simfdata: simulation of survival data

In dscoreMSM: Survival Proximity Score Matching in Multi-State Survival Model

simulation of survival data

Description

function for simulation of survival data assuming the data comes from a parametric coxph model with gamma frailty distribution

Usage

simfdata(n, beta, fvar, bhdist = "weibull", X, fdist = "gamma", ...)

Arguments

n	number of individual
beta	vector of regression coefficient for coxph model
fvar	frailty variance value(currently the function works for gamma frailty only)
bhdist	distribution of survival time at baseline e.g. "weibull","exponential","llogistic"
X	model matrix for the coxPH model with particular choice of beta
fdist	distribution of frailty terms e.g. "gamma"
...	user can assume the shape and scale parameter of baseline survival distribution

Details

The process for simulation of multistate survival data is described in our manuscript. As the process includes transition through different states and it involves simulating survival time in different transition. So we have demonstrated the code for simulation of simple survival model. Suppose we want to simulate a survival data with parametric baseline hazard and parametric frailty model. The hazard model is as follows:

h_i(t)=z_ih_0(t)exp(\textbf{x}_i\beta)\;;i=1,2,3,...,n

where the baseline survival time follow Weibull distribution and the hazard is

h_0(t)=\rho \lambda t^{\rho-1}

. Similarly we can have Gompertz, log logistic distribution. The following are the formula for hazard and cummulative hazard function For exponential: h_0(t)=\lambda and H_0(t)=\lambda t\;\lambda>0 Gompertz: h_0(t)=\lambda exp(\gamma t) and H_0(t)=\frac{\lambda}{\gamma}(exp(\gamma t)-1);\lambda,\gamma>0

Value

simulated survival data for a single transition

Author(s)

Atanu Bhattacharjee, Bhrigu Kumar Rajbongshi and Gajendra K. Vishwakarma

References

Vishwakarma, G. K., Bhattacherjee, A., Rajbongshi, B. K., & Tripathy, A. (2024). Censored imputation of time to event outcome through survival proximity score method. Journal of Computational and Applied Mathematics, 116103;

Bhattacharjee, A., Vishwakarma, G. K., Tripathy, A., & Rajbongshi, B. K. (2024). Competing risk multistate censored data modeling by propensity score matching method. Scientific Reports, 14(1), 4368.

See Also

cphGM

Examples

##
n1<-1000
p1<-2
X1<-matrix(rnorm(n1*p1),n1,p1)
simulated_data<-simfdata(n=1000,beta=c(0.5,0.5),fvar=0.5,
X=X1)
##

dscoreMSM documentation built on April 4, 2025, 12:38 a.m.