Hi, I am currently analysising a counting process form of a cox model allowing for the inclusion of time dependent covariates. An example model I have fitted is
modlqol<-coxph(Surv(Tstart,Tstop,cens.time)~tmt.first+risk +lqol+cluster(id),data=cat) summary(modlqol) My question is quick. I am looking at 1 event (death), and repeated measurements (the time dependent covariate 'lqol') are frequently taken on a subject, so I assume that measurements on the same subject will be correlated. For this reason, I included the cluster(id) term in the model. However, on p70 Therneau and Grambsch, it states 'one concern that often arises is that observations on the same individual are correlated and thus would not be handled by standard methods. This is not actually an issue. .......................' so, does anyone recommend that I include the 'cluster(id)' term or does this only need to be utilised in the situation where there is multiple events (eg in the bladder cancer study by Wei, Lin and Weissfeld) ? I appreciate any help on the matter, Thanks, Zoe ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
