A dataset containing survival data for 5 groups, where part of the effects and baseline hazards are heterogeneous. Each group consists of 100 individuals. The survival time \(T\) for group \(i\) is generated according to the following model: $$ \lambda^{(i)}(t)=\lambda_{0,i}(t)\exp\left(x^\top\beta^{(i)}\right), $$ where \(\lambda_{0,i}(t)\) represents the baseline hazard for group \(i\), \(\beta^{(i)}\) represents the effects for group \(i\), and \(x\) represents the covariates. The covariates \(x=(x_{1},\ldots,x_{20})\) are generated from a multivariate normal distribution with mean 0 and covariance matrix \(\Sigma=I_{20}\). The baseline hazard function is defined as: $$ \lambda_{0,i}(t)=\left\{\begin{array}{ll} t^{2}, & \text{if } i=1,3,5 \\ t, & \text{if } i=2,4. \end{array}\right. $$ The effects are defined as: $$ \beta^{(i)}=\left\{\begin{array}{ll} (0.3,0.3,0.3,0.3,0,\ldots,0), & \text{if } i=1, \\ (0.9,0.9,0.3,0.3,0,\ldots,0), & \text{if } i=2,4, \\ (-0.3,-0.3,0.3,0.3,0,\ldots,0), & \text{if } i=3,5. \end{array}\right. $$ The maximum censoring time is fixed at 2, with an approximate censoring rate of 20%.
Format
A data frame with 500 rows and 24 variables:
- id
Individual identifier, 1-500
- group
Group indicator, 1-5
- time
Survival time
- status
Status indicator, 0=censored, 1=event
- X1
Covariate 1
- X2
Covariate 2
- X3
Covariate 3
- X4
Covariate 4
- X5
Covariate 5
- X6
Covariate 6
- X7
Covariate 7
- X8
Covariate 8
- X9
Covariate 9
- X10
Covariate 10
- X11
Covariate 11
- X12
Covariate 12
- X13
Covariate 13
- X14
Covariate 14
- X15
Covariate 15
- X16
Covariate 16
- X17
Covariate 17
- X18
Covariate 18
- X19
Covariate 19
- X20
Covariate 20