genCPHM {genSurv}R Documentation

Generation of survival data from a Cox Proportional Hazard Model

Description

Generation of survival data from a Cox Proportional Hazard Model.

Usage

genCPHM(n, model.cens, cens.par, beta, covar)

Arguments

n

Sample size.

model.cens

Model for censorship. Possible values are "uniform" and "exponential".

cens.par

Parameter for the censorship distribution. Must be greater than 0.

beta

Regression parameter for the time-fixed covariate.

covar

Parameter for generating the time-fixed covariate. An uniform distribution is used.

Value

An object with two classes, data.frame and CPHM.

Author(s)

Artur Araújo, Luís Meira Machado and Susana Faria

References

Cox, D.R. (1972). Regression models and life tables. Journal of the Royal Statistical Society: Series B, 34(2), 187-202. doi: 10.1111/j.2517-6161.1972.tb00899.x

Meira-Machado L., Faria S. (2014). A simulation study comparing modeling approaches in an illness-death multi-state model. Communications in Statistics - Simulation and Computation, 43(5), 929-946. doi: 10.1080/03610918.2012.718841

Meira-Machado, L., Sestelo M. (2019). Estimation in the progressive illness-death model: a nonexhaustive review. Biometrical Journal, 61(2), 245–263. doi: 10.1002/bimj.201700200

See Also

genCMM, genTDCM, genTHMM.

Examples

cphmdata <- genCPHM(n=1000, model.cens="exponential", cens.par=2, beta= 2, covar=1)
head(cphmdata, n=20L)
library(survival)
fit<-coxph(Surv(time,status)~covariate,data=cphmdata)
summary(fit)

[Package genSurv version 1.0.4 Index]