Time-to-event data, including both survival and censoring times, are created using functions `defSurv`

and `genSurv`

. The survival data definitions require a variable name as well as a specification of a scale value, which determines the mean survival time at a baseline level of covariates (i.e. all covariates set to 0). The Weibull distribution is used to generate these survival times. In addition, covariates (which have been defined previously) that influence survival time can be included in the `formula`

field. Positive coefficients are associated with longer survival times (and lower hazard rates). Finally, the *shape* of the distribution can be specified. A `shape`

value of 1 reflects the *exponential* distribution.

```
# Baseline data definitions
<- defData(varname = "x1", formula = 0.5, dist = "binary")
def <- defData(def, varname = "x2", formula = 0.5, dist = "binary")
def <- defData(def, varname = "grp", formula = 0.5, dist = "binary")
def
# Survival data definitions
set.seed(282716)
<- defSurv(varname = "survTime", formula = "1.5*x1", scale = "grp*50 + (1-grp)*25",
sdef shape = "grp*1 + (1-grp)*1.5")
<- defSurv(sdef, varname = "censorTime", scale = 80, shape = 1)
sdef
sdef
```

```
## varname formula scale shape
## 1: survTime 1.5*x1 grp*50 + (1-grp)*25 grp*1 + (1-grp)*1.5
## 2: censorTime 0 80 1
```

The data are generated with calls to `genData`

and `genSurv`

:

```
# Baseline data definitions
<- genData(300, def)
dtSurv <- genSurv(dtSurv, sdef)
dtSurv
head(dtSurv)
```

```
## id x1 x2 grp survTime censorTime
## 1: 1 0 0 1 9.21 96.0
## 2: 2 0 1 0 25.52 46.8
## 3: 3 0 1 0 604.20 31.6
## 4: 4 1 1 0 23.63 338.4
## 5: 5 1 0 0 108.28 287.6
## 6: 6 0 1 1 8.12 53.4
```

```
# A comparison of survival by group and x1
round(mean(survTime), 1), keyby = .(grp, x1)] dtSurv[,
```

```
## grp x1 V1
## 1: 0 0 156.2
## 2: 0 1 19.0
## 3: 1 0 43.3
## 4: 1 1 14.1
```

Observed survival times and censoring indicators can be generated by defining new fields:

```
<- defDataAdd(varname = "obsTime", formula = "pmin(survTime, censorTime)", dist = "nonrandom")
cdef <- defDataAdd(cdef, varname = "status", formula = "I(survTime <= censorTime)",
cdef dist = "nonrandom")
<- addColumns(cdef, dtSurv)
dtSurv
head(dtSurv)
```

```
## id x1 x2 grp survTime censorTime obsTime status
## 1: 1 0 0 1 9.21 96.0 9.21 TRUE
## 2: 2 0 1 0 25.52 46.8 25.52 TRUE
## 3: 3 0 1 0 604.20 31.6 31.62 FALSE
## 4: 4 1 1 0 23.63 338.4 23.63 TRUE
## 5: 5 1 0 0 108.28 287.6 108.28 TRUE
## 6: 6 0 1 1 8.12 53.4 8.12 TRUE
```

```
# estimate proportion of censoring by x1 and group
round(1 - mean(status), 2), keyby = .(grp, x1)] dtSurv[,
```

```
## grp x1 V1
## 1: 0 0 0.51
## 2: 0 1 0.13
## 3: 1 0 0.37
## 4: 1 1 0.17
```

Here is a Kaplan-Meier plot of the data by the four groups:

```
## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.
```