There are several issues. First the Cox model is not for a binary outcome. It is for a time-to-event outcome whose status (event vs. censored) is binary. Second, split-sample validation does not work well with n < 20000 in the combined sample. Third, reclassification tables are not used to validate models; they are used to compare two models. Fourth, the rms package has several methods for truly validating Cox models. Frank
Petergodsk wrote > Thank you very much to Prof. Harrell for the comment. > > I have fitted a Cox model on one data set and need to validate it on > another dataset with a binary outcome. > > I can't find a way to make the reclassification (or the PredRisk) function > in the PredictABEL package to accept my Cox model. I have used > predictSurvProb to calculate predicted survival which is accepted by the > ImproveProb function, but - as mentioned - not by the reclassification > function in the PredictABEL package. > > Does anyone have a solution? > > Thanks, > Peter Godsk ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/NRI-reclassification-table-improveProb-Cox-tp4653768p4653878.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ [email protected] 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.
