This dataset was generated for a simulation study to evaluate survival models incorporating both continuous and categorical covariates.
Usage
data(sim)Format
A data frame with 6,000 rows and 10 variables:
- id
Integer identifier for each subject.
- time
Observed event or censoring time.
- status
Event indicator: 1 for event, 0 for right-censored.
- x1
First continuous covariate, generated from a bivariate normal distribution.
- x2
Second continuous covariate, also from the bivariate normal distribution.
- x31
First binary categorical covariate, generated from a Bernoulli distribution.
- x42
Dummy variable for level 2 of the second categorical covariate (reference is level 1).
- x43
Dummy variable for level 3 of the second categorical covariate.
- x44
Dummy variable for level 4 of the second categorical covariate.
- group
An integer (1 to 6) indicating the dataset partition group.
Details
The two continuous covariates x1 and x2 were
independently drawn from a bivariate normal distribution. The binary
covariate x31 was generated from a Bernoulli distribution. The
second categorical covariate had four levels and was drawn from a
multinomial distribution, conditional on x31. The final covariates
x42–x44 are dummy variables representing levels 2–4
(level 1 is the reference).
Event times were generated from a mixture of two Weibull distributions with shape parameters 3 and 5, and scale parameters 10 and 20, respectively. Right censoring was imposed using censoring times drawn from an exponential distribution with rate 3.
The true regression coefficients were: $$\boldsymbol{\beta} = (0.15, -0.15, 0.3, 0.3, 0.3, 0.3)^\top$$
The complete dataset includes six subsets: the first three contain 1,500
observations each, and the remaining three contain 500 each. These subsets
are indicated by the group variable.
Examples
data(sim)
head(sim)
#> id time status x1 x2 x31 x42 x43 x44 group
#> 1 1 0.09887412 0 10.958910 5.938538 1 0 0 1 1
#> 2 2 0.05130399 0 7.499272 6.305020 1 1 0 0 1
#> 3 3 0.26820027 1 4.589824 4.250194 1 0 0 1 1
#> 4 4 0.14401458 1 4.528155 5.301456 1 0 1 0 1
#> 5 5 0.24992644 0 5.469901 5.624268 0 0 0 1 1
#> 6 6 0.40221177 1 5.063252 6.157249 1 0 0 1 1