Thanks Terry, Re: the second case (predicting from a null model with a newdata= argument), I agree that it looks a bit over the top for such a straight forward computation, so maybe it is more a wish than anything else. In this one instance, this computation is embedded in a wider multi-state simulation in Epi::simLexis() where transition hazards are modeled as functions of covariates via Cox proportional hazards, and a subset of transitions happen not to depend on any covariate, thus the null model(s). There are ways to circumvent this special case within Epi::simLexis(), so even in this one example I wouldn't consider it high priority at all. But maybe it would be nice to have.
On Sat, Oct 1, 2016 at 10:44 PM, Therneau, Terry M., Ph.D. <thern...@mayo.edu> wrote: > I'm off on vacation and checking email only intermittently. > Wrt the offset issue, I expect that you are correct. This is not a case that > I had ever envisioned, and so was not on my "list" when writing the code and > certainly has no test case. That does not mean that it shouldn't work, just > that I am not shocked to see it. I will look into this. > > For the second case of a NULL model I am less sympathetic. This is, in > theory, just reading off values from a Nelson hazard estimate at specific > time points; using a coxph call to do so is a case of swatting a fly with a > hammer. A bit more background might make me more excited about extending > the code to this case. > > Terry Therneau ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
