gof.phreg: GOF for Cox PH regression

In mets: Analysis of Multivariate Event Times

GOF for Cox PH regression

Description

Cumulative score process residuals for Cox PH regression p-values based on Lin, Wei, Ying resampling.

Usage

## S3 method for class 'phreg'
gof(object, n.sim = 1000, silent = 1, robust = NULL, ...)

Arguments

object	is phreg object
n.sim	number of simulations for score processes
silent	to show timing estimate will be produced for longer jobs
robust	to control wether robust dM_i(t) or dN_i are used for simulations
...	Additional arguments to lower level funtions

Author(s)

Thomas Scheike and Klaus K. Holst

Examples

library(mets)
data(sTRACE)

m1 <- phreg(Surv(time,status==9)~vf+chf+diabetes,data=sTRACE) 
gg <- gof(m1)
gg
par(mfrow=c(1,3))
plot(gg)

m1 <- phreg(Surv(time,status==9)~strata(vf)+chf+diabetes,data=sTRACE) 
## to get Martingale ~ dN based simulations
gg <- gof(m1)
gg

## to get Martingale robust simulations, specify cluster in  call 
sTRACE$id <- 1:500
m1 <- phreg(Surv(time,status==9)~vf+chf+diabetes+cluster(id),data=sTRACE) 
gg <- gof(m1)
gg

m1 <- phreg(Surv(time,status==9)~strata(vf)+chf+diabetes+cluster(id),data=sTRACE) 
gg <- gof(m1)
gg

mets documentation built on May 29, 2024, 3:51 a.m.