Sorry for being impatient but is there really no way of doing this at all? It's quite urgent so any help is very much appreciated. Thank you.
RWilliam wrote: > > Hello, > > I just started using R to do epidemiologic simulation research using the > Cox proportional hazard model. I have 2 covariates X1 and X2 which I want > to model as h(t,X)=h0(t)*exp(b1*X1+b2*X2). I assume independence of X from > t. > > After I simulate Time and Censor data vectors denoting the censoring time > and status respectively, I can call the following function to fit the data > into the Cox model (a is a data.frame containing 4 columns X1, X2, Time > and Censor): > b = coxph (Surv (Time, Censor) ~ X1 + X2, data = a, method = "breslow"); > > Now the purpose of me doing simulation is that I have another mechanism to > generate the number b2. From the given b2 (say it's 4.3), Cox model can be > fit to generate b1 and check how feasible the new model is. Thus, my > question is, how do I specify such a model that is partially completed (as > in b2 is known). I tried things like Surv(Time,Censor)~X1+4.3*X2, but it's > not working. Thanks very much. > -- View this message in context: http://old.nabble.com/How-do-I-specify-a-partially-completed-survival-analysis-model--tp26421391p26441878.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.
