GOF for Cox PH regression
Cumulative score process residuals for Cox PH regression p-values based on Lin, Wei, Ying resampling.
## S3 method for class 'phreg' gof(object, n.sim = 1000, silent = 1, robust = NULL, ...)
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 |
Thomas Scheike and Klaus K. Holst
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
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