CRAN Package Check Results for Package stremr

Last updated on 2018-02-17 20:46:48 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.4 22.14 202.18 224.32 NOTE
r-devel-linux-x86_64-debian-gcc 0.4 17.81 156.86 174.67 NOTE
r-devel-linux-x86_64-fedora-clang 0.4 269.38 NOTE
r-devel-linux-x86_64-fedora-gcc 0.4 255.24 NOTE
r-devel-windows-ix86+x86_64 0.4 33.00 364.00 397.00 OK
r-patched-linux-x86_64 0.4 14.17 205.22 219.39 NOTE
r-patched-solaris-x86 0.4 337.70 ERROR
r-release-linux-x86_64 0.4 13.21 201.05 214.26 NOTE
r-release-windows-ix86+x86_64 0.4 36.00 413.00 449.00 OK
r-release-osx-x86_64 0.4 ERROR
r-oldrel-windows-ix86+x86_64 0.4 22.00 483.00 505.00 OK
r-oldrel-osx-x86_64 0.4 ERROR

Check Details

Version: 0.4
Check: compiled code
Result: NOTE
    File ‘stremr/libs/stremr.so’:
     Found no calls to: ‘R_registerRoutines’, ‘R_useDynamicSymbols’
    
    It is good practice to register native routines and to disable symbol
    search.
    
    See ‘Writing portable packages’ in the ‘Writing R Extensions’ manual.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [210s/247s]
    Running the tests in ‘tests/test-all.R’ failed.
    Complete output:
     > ## unit tests will not be done if RUnit is not available
     > # setwd("..")
     > # getwd()
     > # library(RUnit)
     > if(require("RUnit", quietly=TRUE)) {
     + ## --- Setup ---
     +
     + pkg <- "stremr" # <-- Tested package name
     +
     + if(Sys.getenv("RCMDCHECK") == "FALSE") {
     + ## Path to unit tests for standalone running under Makefile (not R CMD check)
     + ## PKG/tests/../inst/unitTests
     + # path <- file.path(getwd(), "..", "inst", "unitTests")
     + } else {
     + ## Path to unit tests for R CMD check
     + ## PKG.Rcheck/tests/../PKG/unitTests
     + # path <- system.file(package=pkg, "RUnit")
     +
     + # REPLACED WITH:
     + path <- file.path(getwd(), "RUnit")
     + }
     +
     + cat("\nRunning unit tests\n")
     + print(list(pkg=pkg, getwd=getwd(), pathToUnitTests=path))
     +
     + library(package=pkg, character.only=TRUE)
     +
     + ## If desired, load the name space to allow testing of private functions
     + ## if (is.element(pkg, loadedNamespaces()))
     + ## attach(loadNamespace(pkg), name=paste("namespace", pkg, sep=":"), pos=3)
     + ##
     + ## or simply call PKG:::myPrivateFunction() in tests
     +
     + ## --- Testing ---
     +
     + ## Define tests
     + test.suite <- defineTestSuite(name=paste(pkg, "unit testing"),
     + # dirs="./RUnit",
     + dirs=path,
     + testFileRegexp = "^RUnit_tests_+",
     + testFuncRegexp = "^test.+",
     + rngKind = "Marsaglia-Multicarry",
     + rngNormalKind = "Kinderman-Ramage")
     + ## Run
     + tests <- runTestSuite(test.suite)
     +
     + ## Default report name
     + pathReport <- file.path(path, "report")
     +
     + ## Report to stdout and text files
     + cat("------------------- UNIT TEST SUMMARY ---------------------\n\n")
     + printTextProtocol(tests, showDetails=FALSE)
     + printTextProtocol(tests, showDetails=FALSE,
     + fileName=paste0(pathReport, "Summary.txt"))
     + printTextProtocol(tests, showDetails=TRUE,
     + fileName=paste0(pathReport, ".txt"))
     + ## Report to HTML file
     + printHTMLProtocol(tests, fileName=paste0(pathReport, ".html"))
     +
     + ## Return stop() to cause R CMD check stop in case of
     + ## - failures i.e. FALSE to unit tests or
     + ## - errors i.e. R errors
     + tmp <- getErrors(tests)
     + if(tmp$nFail > 0 | tmp$nErr > 0) {
     + stop(paste("\n\nunit testing failed (#test failures: ", tmp$nFail,
     + ", #R errors: ", tmp$nErr, ")\n\n", sep=""))
     + }
     + } else {
     + warning("cannot run unit tests -- package RUnit is not available")
     + }
    
     Running unit tests
     $pkg
     [1] "stremr"
    
     $getwd
     [1] "/home/ripley/R/packages/tests32/stremr.Rcheck/tests"
    
     $pathToUnitTests
     [1] "/home/ripley/R/packages/tests32/stremr.Rcheck/tests/RUnit"
    
    
    
     Executing test function test.GenericModelPredict ... Loading required package: data.table
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.6829138 1.4512950 -0.4353432 0.5852046
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "catA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: catA"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA, catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4666 4621 4702
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 2 NA 1 NA
     [3,] 1 NA 1 NA
     [4,] 3 NA 1 NA
     [5,] 1 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -9.762950e-08 2.155173e-06 NA
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4666 4621 4702
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 2 NA 1 NA
     [3,] 1 NA 1 NA
     [4,] 3 NA 1 NA
     [5,] 1 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -3.738646e-08 -2.346217e-07 -2.013073e-07
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     fit for catA var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     done successfully.
    
    
    
     Executing test function test.Nsamp.n.test ... done successfully.
    
    
    
     Executing test function test.options ... [1] "Possible `stremr` options:"
     [1] "fit.package" "fit.algorithm" "bin.method"
     [4] "nbins" "maxncats" "maxNperBin"
     [7] "lower_bound_zero_Q" "skip_update_zero_Q"
     Error in stremrOptions("blahblah") :
     blahblah: this options does not exist
     Error in stremrOptions("blahblah", 5) : Invalid option name: blahblah
     Error in if (!(fit.algorithm %in% allowed.fit.algorithm)) stop("fit.algorithm must be one of: " %+% :
     argument is of length zero
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "blahblah", :
     fit.algorithm must be one of: glm, gbm, randomForest, deeplearning
     Error in set_all_stremr_options(fit.package = "blahblah", fit.algorithm = "glm", :
     fit.package must be one of: speedglm, glm, h2o
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "glm", :
     bin.method must be one of: equal.mass, equal.len, dhist
     $fit.package
     [1] "speedglm"
    
     $fit.algorithm
     [1] "glm"
    
     $bin.method
     [1] "equal.mass"
    
     $nbins
     [1] 10
    
     $maxncats
     [1] 20
    
     $maxNperBin
     [1] 500
    
     $lower_bound_zero_Q
     [1] TRUE
    
     $skip_update_zero_Q
     [1] TRUE
    
     done successfully.
    
    
    
     Executing test function test.regressionCases ... done successfully.
    
    
    
     Executing test function test.t.error ... done successfully.
    
    
    
     Executing test function test.DataStorageClass ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in OData$get.outvar(var = "blah") :
     requested variable blah does not exist in DataStorageClass!
     done successfully.
    
    
    
     Executing test function test.error.fits.stratify ... Error in create_subset_expr(outvars = res$outvars, stratify.EXPRS = stratify.EXPRS) :
     Could not locate the appropriate regression variable(s) within the supplied stratification list stratify_CENS, stratify_TRT or stratify_MONITOR.
     The regression outcome variable(s) specified in gform_CENS, gform_TRT or gform_MONITOR were: ( 'C,TI' )
     However, the item names in the matching stratification list were: ( 'wrongC,TI,N' )
     done successfully.
    
    
    
     Executing test function test.helperfuns ... done successfully.
    
    
    
     Executing test function test.model.fits.stratify ... done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.19067146 NA 0.43343872 -0.01789425
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01340964 NA NA -0.03245807 -0.01185101
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01135495 NA NA -0.02269938 -0.01321850
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 1,t > 0 & C == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 1 & TI == 1,t > 0 & C == 1 & TI == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA NA NA NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA 0.4924641 0.1270091 -0.1911502
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0L & TI.tminus1 == 0L,t > 0L & TI.tminus1 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01467019 -0.45533330 NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01135495 -0.02269938 -0.01321850 NA NA
     fit for N var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 1.092843e-07 1.158713e-07 1.320318e-07
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "performing prediction for outcome based on stratified model: TI"
     done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR2 ... Loading required package: magrittr
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "CatC"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: CatC"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC, CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,(t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L),(t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L),(t > 0L) & (barTIm1eq0 == 1L))"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: CatC"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.1487960 0.1616531
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.13719779 -0.08098814
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -2.9593646 0.5614693
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -4.89784 -15.66823
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     fit for CatC var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.1141458 0.9100488 2.1714524 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 2.444839e-12 2.082888e-12 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "N"
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     done successfully.
    
    
    
     Executing test function test.buildingblocks ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in getIPWeights(OData = OData, intervened_TRT = "TI.set1", rule_name = "TI1") :
     ...cannot locate propensity scores in 'OData' object - must run fitPropensity(...) prior to calling this function
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.198768e-13 -5.125570e-14
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -6.143963e-14 -2.839781e-14
     fit for C var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.465039e+00 -4.324378e+00 -4.012934e+00 -1.166619e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -6.871355e+14 -4.884654e+14 -6.732368e+00 -6.414551e+00
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.490327e+15 -3.057464e+15 -3.089228e+00 -4.070768e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.097356e+00 -1.444049e+01 -3.626218e+00 -4.172158e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.928687e+00 -3.921940e+00 -4.645602e+00 -3.410729e+00
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.462573e-17 2.944089e-16 2.828261e-15 7.293270e+00
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     6.561300e+01 4.445403e+02 2.942740e-14 3.696352e-14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.030033e+02 7.899748e+02 8.616021e-19 3.997853e-18
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.040425e-18 4.879654e-08 1.004232e-17 7.554828e-18
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     1.455016e-18 1.499928e-17 3.341834e-16 9.527988e-16
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.421742e-15 3.237747e-15 6.931219e-15 3.336980e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     7.563694e+14 1.183848e+15 5.042360e-15 7.041551e-15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     1.830248e+14 5.408850e+14 4.887755e-16 5.013825e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     6.663849e-15 1.000001e+00 3.001987e-15 2.794958e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     2.080482e-15 2.142088e-15 8.589764e-15 1.696652e-15
     [1] "Should all be very small: "
     [1] 3.995817e-17 2.563398e-18 1.217398e-16 1.217398e-16 1.217398e-16
     [6] 1.217398e-16 1.130589e-16 1.270720e-16 1.270720e-16 1.270720e-16
     [11] 1.270720e-16 1.270720e-16 1.270720e-16 1.270720e-16 1.270720e-16
     [16] 1.270720e-16
     [1] "Should all be very small: "
     [1] 1.939833e-17 6.272759e-17 1.621637e-16 4.951408e-07 4.823035e-07
     [6] 4.749798e-07 4.737188e-07 4.645200e-07 4.601013e-07 4.557247e-07
     [11] 4.513896e-07 4.470959e-07 4.328058e-07 4.189726e-07 4.055814e-07
     [16] 3.926183e-07
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.479625e+00 -4.224521e+15 -4.040682e+15 -3.195295e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -3.082898e+15 -2.778817e+15 -3.052026e+15 -3.796228e+15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.715406e+15 -1.534193e+15 -3.048470e+00 -4.020852e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.106498e+00 -1.007712e+01 -3.450746e+00 -4.160778e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.909203e+00 -4.008647e+00 -4.781623e+00 -3.422484e+15
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     1.372220e-15 3.892340e+00 1.153066e+02 3.014492e+03
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.096739e+04 2.100000e+04 1.300000e+04 5.000000e+03
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.700000e+04 1.000000e+04 2.216689e-17 1.053539e-17
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     2.234741e-17 1.670762e-05 2.646152e-17 1.029625e-16
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     5.181238e-18 1.142027e-16 3.446043e-04 2.159757e+02
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     2.028144e-14 5.581563e+13 7.715289e+13 2.180508e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.367837e+14 2.874638e+14 2.419289e+14 1.178953e+14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.980323e+14 4.949011e+14 9.307628e-15 6.147405e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.082937e-15 1.000042e+00 1.067397e-15 4.119857e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     5.948334e-16 8.761861e-16 1.571325e-04 1.801860e+14
     [1] "Should all be very small: "
     [1] 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17
     [6] 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17
     [11] 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17
     [16] 8.388493e-17
     [1] "Should all be very small: "
     [1] 3.995437e-16 2.944031e-16 1.817868e-16 3.877971e-05 3.758736e-05
     [6] 3.701017e-05 3.690999e-05 3.625173e-05 3.706763e-05 3.786745e-05
     [11] 3.865142e-05 3.941974e-05 3.941974e-05 3.941974e-05 3.941974e-05
     [16] 3.941974e-05
     Error in process_opt_wts(wts_data_used, weights, nodes) :
     input 'weights' must be a data.table with 3 columns, two of which must be named as: 'ID' and 't'.
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.8682574 0.2154351 3.3021509 0.4033691 NA 0.7501467 NA
     [1] "Surv est: 0.983758322675102"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01624"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -4.67474313 0.19724908 2.21184261 -0.09839186 0.76483183 0.36869687
     TI.tminus1
     -0.98759997
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.48082464 0.25283340 2.46508499 0.04786835 NA -0.43706261
     TI.tminus1
     NA
     [1] "Surv est: 0.969902221464484"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.0301"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.8073588 -1.1071567 1.3574257 -0.4540453 0.6083749 0.3767599 -1.4726757
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7570081 -0.3346276 1.4801253 -0.3532999 0.5055449 -0.5127511 -0.6589153
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.90325161 -0.07708853 2.01607750 -0.02829320 NA -0.32644563
     TI.tminus1
     NA
     [1] "Surv est: 0.953782240282528"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04622"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.2729961 0.6045142 2.3185601 -1.4506484 0.4525435 -1.0902410 -1.7027505
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.45925760 -0.49121038 1.40054082 -0.35287095 0.50934192 -0.02283871
     TI.tminus1
     -1.28687470
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8442520 -0.1010111 1.5056775 -0.2372471 0.4546915 -0.4782690 -0.6244729
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.94053966 0.04857403 1.99765895 0.01058704 NA -0.32554792
     TI.tminus1
     NA
     [1] "Surv est: 0.953681572539541"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04632"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.0863662 1.4415952 1.1242617 -0.4941329 -0.1391926 -0.8298997 -0.6156850
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1883548 1.2010569 1.3144619 -0.3947993 0.1333006 -0.9913184 -0.5170650
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.11978976 0.36019767 1.14780785 -0.23837798 0.37263297 -0.05869163
     TI.tminus1
     -0.85675524
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.6602088 0.3624027 1.3288288 -0.1996436 0.3619692 -0.4185487 -0.4804042
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.757594710 0.346812991 1.758549008 0.002438552 NA -0.302239540
     TI.tminus1
     NA
     [1] "Surv est: 0.943575229684676"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.05642"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.694637 0.368584 3.290803 -0.666631 NA NA NA
     [1] "tmle update: -0.00149135496809922"
     [1] "Surv est: 0.984107401301778"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01589"
     [1] "...empirical mean of the estimated EIC: -3.0907990045453e-05"
     [1] "...estimated TMLE variance: 2.41999050417123e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8004930 0.9282348 0.6879804 -0.5514791 0.7438655 NA NA
     [1] "tmle update: 0.0727160966327068"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6000572 0.5722892 2.2618565 -0.7563574 NA NA NA
     [1] "tmle update: -0.00223570491646532"
     [1] "Surv est: 0.969834495012909"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.03017"
     [1] "...empirical mean of the estimated EIC: -6.07101133764973e-05"
     [1] "...estimated TMLE variance: 6.61356670225727e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9817186 -17.2807447 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595614761733"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771607969"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300657587"
     [1] "Surv est: 0.951909613102674"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.00010436571628225"
     [1] "...estimated TMLE variance: 0.000251078927354862"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595625433471"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771369513"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300648762"
     [1] "Surv est: 0.95190961310293"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.000104365720571851"
     [1] "...estimated TMLE variance: 0.000251078927359577"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147885716"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449204439"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.0044898089735453"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661689564"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377143477277"
     [1] "Surv est: 0.925542187707399"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -0.000520790968265632"
     [1] "...estimated TMLE variance: 0.00803708770988043"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595441256697"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715758304585"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.0033447030197795"
     [1] "Surv est: 0.951909613112289"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -1.65538533979758e-05"
     [1] "...estimated TMLE variance: 8.3806787779791e-06"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147869959"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449202842"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980955099559"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661764049"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377139578662"
     [1] "Surv est: 0.925542187729508"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -8.12433860103577e-05"
     [1] "...estimated TMLE variance: 0.00019629047768188"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: 0.00455038396959827"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5351943 -0.2698513 0.0819634 -1.1897532 1.1194722 NA NA
     [1] "tmle update: 0.00148791277372818"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.9037005 0.1316045 1.9048099 -0.7888752 NA NA NA
     [1] "tmle update: 0.00387375452111821"
     [1] "Surv est: 0.952423126954576"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04758"
     [1] "...empirical mean of the estimated EIC: -3.11352727229608e-05"
     [1] "...estimated TMLE variance: 4.05438882728483e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.00435566075945477"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.1065413 0.4996280 0.7537557 1.4595663 0.1268353 NA NA
     [1] "tmle update: -6.23201904597049e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.365723662 -0.465839994 0.005840225 -0.509288785 0.596038204 NA
     TI.tminus1
     NA
     [1] "tmle update: -4.44504971164046e-10"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.88176714 0.08310961 0.32781298 -0.75064933 0.51647978 NA
     TI.tminus1
     NA
     [1] "tmle update: 5.99583600832673e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.5397115 0.1898817 1.5664979 -0.5505100 NA NA NA
     [1] "tmle update: 0.00279335492939026"
     [1] "Surv est: 0.931389922902869"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.06861"
     [1] "...empirical mean of the estimated EIC: -3.04000131367626e-05"
     [1] "...estimated TMLE variance: 5.41527268962014e-05"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     done successfully.
    
    
    
     Executing test function test.speedglm.allestimators10Kdata ... [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     Timing stopped at: 43.17 1.559 52.2
     Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     4: glm.fit: algorithm did not converge
     5: glm.fit: algorithm did not converge
     6: glm.fit: algorithm did not converge
     7: glm.fit: algorithm did not converge
     8: glm.fit: algorithm did not converge
     9: In readChar(con, 5L, useBytes = TRUE) :
     cannot open compressed file '/tmp/RtmpvAaGYu/sim.data.example.fup.Rd', probable reason 'No such file or directory'
     done successfully.
    
    
    
     Executing test function test.speedglm.stochastic.TMLE.NDE.1Kdata ... done successfully.
    
    
    
     Executing test function test.GCOMP.TMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.directRegressionDefn.10Kdata ... done successfully.
    
    
    
     Executing test function test.iterTMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.ContinModel ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "continA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "ContinModel outcome: continA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA_B.1, continA_B.2, continA_B.3, continA_B.4, continA_B.5, continA_B.6, continA_B.7, continA_B.8, continA_B.9, continA_B.10, continA_B.11, continA_B.12, continA_B.13, continA_B.14, continA_B.15, continA_B.16, continA_B.17, continA_B.18, continA_B.19, continA_B.20, continA_B.21, continA_B.22, continA_B.23, continA_B.24, continA_B.25, continA_B.26, continA_B.27, continA_B.28, continA_B.29"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 29"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for continuous outcome: continA"
     [1] "freq counts by bin for continuous outcome: "
    
     2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
     519 518 518 518 518 518 518 518 518 518 518 518 518 519 518 518 518 518 518 518 518 518 518 518 518
     27 28
     518 519
     [1] "binned dataset: "
     continA_B.1 continA_B.2 continA_B.3 continA_B.4 continA_B.5 continA_B.6 continA_B.7
     [1,] 15 0 0 0 0 0 0 0
     [2,] 17 0 0 0 0 0 0 0
     [3,] 20 0 0 0 0 0 0 0
     [4,] 16 0 0 0 0 0 0 0
     [5,] 14 0 0 0 0 0 0 0
     continA_B.8 continA_B.9 continA_B.10 continA_B.11 continA_B.12 continA_B.13 continA_B.14
     [1,] 0 0 0 0 0 0 0
     [2,] 0 0 0 0 0 0 0
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 0 0 0 0 0
     [5,] 0 0 0 0 0 0 1
     continA_B.15 continA_B.16 continA_B.17 continA_B.18 continA_B.19 continA_B.20 continA_B.21
     [1,] 1 NA NA NA NA NA NA
     [2,] 0 0 1 NA NA NA NA
     [3,] 0 0 0 0 0 1 NA
     [4,] 0 1 NA NA NA NA NA
     [5,] NA NA NA NA NA NA NA
     continA_B.22 continA_B.23 continA_B.24 continA_B.25 continA_B.26 continA_B.27 continA_B.28
     [1,] NA NA NA NA NA NA NA
     [2,] NA NA NA NA NA NA NA
     [3,] NA NA NA NA NA NA NA
     [4,] NA NA NA NA NA NA NA
     [5,] NA NA NA NA NA NA NA
     continA_B.29
     [1,] NA
     [2,] NA
     [3,] NA
     [4,] NA
     [5,] NA
     [1] "fitting the model: P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 -1.172459e-11 -1.310221e-11 -2.568646e-11
     [1] "fitting the model: P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.23128648 -0.11313601 0.11405562 -0.07044987
     [1] "fitting the model: P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.14785170 0.02684205 0.03299729 -0.15662838
     [1] "fitting the model: P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.188109547 0.320708670 -0.163340697 -0.000298704
     [1] "fitting the model: P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.2980005 0.0308173 0.1299232 0.2346028
     [1] "fitting the model: P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.11091914 -0.11434581 -0.06788767 0.08245927
     [1] "fitting the model: P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.0701047 -0.1509282 -0.1808824 0.1364665
     [1] "fitting the model: P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.98396117 0.05728465 -0.17813569 0.02804064
     [1] "fitting the model: P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.90240304 0.00810316 -0.07939997 -0.05267888
     [1] "fitting the model: P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.017412020 0.134262699 0.008309693 0.198551052
     [1] "fitting the model: P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.88525312 0.19256595 -0.09088628 0.08746734
     [1] "fitting the model: P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.81165567 -0.06088360 0.15533571 0.02240088
     [1] "fitting the model: P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.62261909 0.03784443 -0.20056852 -0.10155399
     [1] "fitting the model: P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.626398992 0.116381433 -0.008309704 -0.046400004
     [1] "fitting the model: P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.58361306 0.07961199 -0.04198233 0.03775529
     [1] "fitting the model: P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.46714900 0.17513284 0.00294148 -0.07348630
     [1] "fitting the model: P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.37293612 0.08123540 -0.09665356 -0.02816619
     [1] "fitting the model: P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.19541912 0.06339645 -0.17387872 -0.15657362
     [1] "fitting the model: P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.276794997 -0.002649881 0.054801454 0.124546169
     [1] "fitting the model: P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.10698864 -0.07678193 0.03338096 0.05226468
     [1] "fitting the model: P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.091511528 -0.039326354 0.008342352 0.266395925
     [1] "fitting the model: P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.74373933 -0.08583273 -0.13869214 -0.02344738
     [1] "fitting the model: P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.61764711 -0.10252427 0.13081681 -0.01927699
     [1] "fitting the model: P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.4054473 -0.1801076 -0.2033977 0.1443032
     [1] "fitting the model: P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.0819609033 -0.0576054096 -0.0531447549 0.0001162045
     [1] "fitting the model: P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.60994894 -0.38467211 -0.24123403 0.01168922
     [1] "fitting the model: P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.005793123 -0.321032533 0.242836533 -0.022375849
     [1] "fitting the model: P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 3.547283e-07 4.545286e-08 -5.045755e-07
     [1] "fitting the model: P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for outcome continA succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for continuous outcome: continA"
     [1] "performing prediction for continuous outcome: continA"
     done successfully.
    
     ------------------- UNIT TEST SUMMARY ---------------------
    
     RUNIT TEST PROTOCOL -- Fri Feb 16 14:17:45 2018
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-patched-solaris-x86

Version: 0.4
Check: package dependencies
Result: NOTE
    Package suggested but not available for checking: ‘devtools’
Flavor: r-release-osx-x86_64

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [167s/242s]
    Running the tests in ‘tests/test-all.R’ failed.
    Last 13 lines of output:
     RUNIT TEST PROTOCOL -- Mon Apr 3 00:44:25 2017
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-release-osx-x86_64

Version: 0.4
Check: tests
Result: ERROR
    Running the tests in ‘tests/test-all.R’ failed.
    Last 13 lines of output:
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-oldrel-osx-x86_64