SemiCompRisks: Hierarchical Models for Parametric and Semi-Parametric Analyses of Semi-Competing Risks Data

Hierarchical multistate models are considered to perform the analysis of independent/clustered semi-competing risks data. The package allows to choose the specification for model components from a range of options giving users substantial flexibility, including: accelerated failure time or proportional hazards regression models; parametric or non-parametric specifications for baseline survival functions and cluster-specific random effects distribution; a Markov or semi-Markov specification for terminal event following non-terminal event. While estimation is mainly performed within the Bayesian paradigm, the package also provides the maximum likelihood estimation approach for several para- metric models. The package also includes functions for univariate survival analysis as complementary analysis tools.

Version: 2.8
Depends: MASS, survival, R (≥ 3.3.0)
Suggests: R.rsp
Published: 2018-01-03
Author: Kyu Ha Lee, Catherine Lee, Danilo Alvares, and Sebastien Haneuse
Maintainer: Kyu Ha Lee <klee at hsph.harvard.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: Survival
CRAN checks: SemiCompRisks results

Downloads:

Reference manual: SemiCompRisks.pdf
Vignettes: This document presents a series of vignettes for the models available in SemiCompRisks package.
Package source: SemiCompRisks_2.8.tar.gz
Windows binaries: r-devel: SemiCompRisks_2.8.zip, r-release: SemiCompRisks_2.8.zip, r-oldrel: SemiCompRisks_2.8.zip
OS X El Capitan binaries: r-release: SemiCompRisks_2.8.tgz
OS X Mavericks binaries: r-oldrel: SemiCompRisks_2.8.tgz
Old sources: SemiCompRisks archive

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