I have a question about Cox's partial likelihood approximations in "coxph" function of "survival package (and in SAS as well) in the presence of tied events generated by grouping continuous event times into intervals. I am processing estimations for recurrent events with time-dependent covariates in the Andersen and Gill approach of Cox's model.
If I have understood Breslow's and Efron's approximations correctly, they consist in modifying the denominators of the contributing likelihood term when we do not know the order of occurrence of the events. This order is important only if the tied events are associated to a diferent value of the covariate. I would like to know if the "breslow" and "efron" options still modify the initial denominators of the terms when they correspond to the same covariate. Especially, whithin the same trajectory of the observed process (the same individual), the covariate is measured once for each tied events. To my mind, we would introduce a useless bias in this case since the initial partial likelihood is true. Thank you. -- View this message in context: http://r.789695.n4.nabble.com/Re-Cox-model-approximaions-was-comparing-SAS-and-R-survival-tp3686543p4526443.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org 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.
