svylogrank {survey} | R Documentation |
Computes a weighted version of the logrank and stratified logrank tests for comparing two or more survival distributions. The generalization to complex samples is based on the characterization of the logrank test as the score test in a Cox model. Under simple random sampling with replacement, this function is almost identical to the robust score test in the survival package.
svylogrank(formula, design, ...)
formula |
Model formula with a single predictor and optionally a |
design |
A survey design object |
... |
for future expansion. |
A vector containing the z-statistic for comparing each level of the variable to the lowest, the chisquared statistic for the logrank test, and the p-value.
library("survival") data(nwtco) ## stratified on case status dcchs<-twophase(id=list(~seqno,~seqno), strata=list(NULL,~rel), subset=~I(in.subcohort | rel), data=nwtco, method="simple") svylogrank(Surv(edrel,rel)~factor(stage),design=dcchs) data(pbc, package="survival") pbc$randomized <- with(pbc, !is.na(trt) & trt>0) biasmodel<-glm(randomized~age*edema,data=pbc) pbc$randprob<-fitted(biasmodel) dpbc<-svydesign(id=~1, prob=~randprob, strata=~edema, data=subset(pbc,randomized)) svylogrank(Surv(time,status==2)~trt,design=dpbc) rpbc<-as.svrepdesign(dpbc) svylogrank(Surv(time,status==2)~trt,design=rpbc)