simcoxph: Simulate survival data and fit models

In frailtySurv: General Semiparametric Shared Frailty Model

Simulate survival data and fit models

Description

Generates simulated clustered survival data by repeatedly generating data, using a shared frailty model, and fitting the models. Respective arguments are passed to genfrail and coxph, and the resulting parameter estimates are aggregated and summarized.

This function is similar to simfrail, except models are fitted using the coxph.

Usage

simcoxph(reps, genfrail.args, coxph.args, Lambda.times, cores = 0)

Arguments

reps	number of times to repeat the simulation
genfrail.args	list of arguments to pass to genfrail
coxph.args	list of arguments to pass to coxph
Lambda.times	vector of time points to obtain baseline hazard estimates at
cores	integer; if > 0, the number of cores to use; if < 0, the number of cores not to use; if 0, use all available cores

Value

A simcoxph object that is essentially a data.frame of the resulting parameter estimates. Each row is a single run, and columns are as follows.

seed	the seed used for the run
runtime	the time it took to fit the model
N	number of clusters
mean.K	average cluster size
cens	empirical censorship
beta	true regression coefficients
hat.beta	estimated regression coefficients
se.beta	standard error of each regression coefficient
theta	true frailty distribution parameters
hat.theta	estimated frailty distribution parameters
se.theta	standard error of each frailty distribution parameter (NA since coxph does not currently provide this.)
Lambda	true cumulative baseline hazard at each Lambda.times point
hat.Lambda	estimated cumulative baseline hazard at each Lambda.times point
se.Lambda	standard error at each Lambda.times point (NA since coxph does not currently provide this)

Author(s)

John. V Monaco, Malka Gorfine, Li Hsu

See Also

coxph, genfrail, simfrail

Examples

## Not run: 
sim <- simcoxph(reps=100,
                genfrail.args=alist(
                  N=50, K=2,
                  beta=c(log(2),log(3)), 
                  frailty="gamma", theta=2,
                  Lambda_0 = function(t, tau=4.6, C=0.01) (C*t)^tau), 
                coxph.args=alist(
                  formula=Surv(time, status) ~ Z1 + Z2 + cluster(family), 
                  frailty="gamma"),
                Lambda.times=1:120, cores = 0)

# Summarize the results
summary(sim)

# Plot the residuals
plot(sim, "residuals")

## End(Not run)

frailtySurv documentation built on Aug. 14, 2023, 1:06 a.m.