svycoxph {survey} | R Documentation |
Fit a proportional hazards model to data from a complex survey design, with inverse-probability weighting and with standard errors corrected for cluster sampling.
svycoxph(formula, design,subset=NULL, ...)
formula |
Model formula. Any cluster() terms will be ignored. |
design |
survey.design object. Must contain all variables
in the formula |
subset |
Expression to select a subpopulation |
... |
Other arguments passed to coxph . |
The main difference between this function and coxph
in the
survival package is that this function accounts for the reduction in
variance from stratified sampling and the increase in variance from
having only a small number of clusters.
Note that strata
terms in the model formula describe subsets that
have a separate baseline hazard function and need not have anything to
do with the stratification of the sampling.
An object of class svycoxph
.
Thomas Lumley
Binder DA. (1992) Fitting Cox's proportional hazards models from survey data. Biometrika 79: 139-147
## Somewhat unrealistic example of nonresponse bias. data(pbc, package="survival") biasmodel<-glm(I(trt>0)~age*edema,data=pbc) pbc$randprob<-fitted(biasmodel) dpbc<-svydesign(id=~1, prob=~randprob, strata=~edema, data=subset(pbc,trt>0)) rpbc<-as.svrepdesign(dpbc) svycoxph(Surv(time,status)~log(bili)+protime+alb,design=dpbc) svycoxph(Surv(time,status)~log(bili)+protime+alb,design=rpbc)