Indeed, from the predict() function of the coxph you cannot get directly "time" predictions, but only linear and exponential risk scores. This is because, in order to get the time, a baseline hazard has to be computed and it is not straightforward since it is implicit in the Cox model.
2010/11/11 David Winsemius <dwinsem...@comcast.net>: > > On Nov 11, 2010, at 3:44 AM, Michael Haenlein wrote: > >> Dear all, >> >> I'm struggling with predicting "expected time until death" for a coxph and >> survreg model. >> >> I have two datasets. Dataset 1 includes a certain number of people for >> which >> I know a vector of covariates (age, gender, etc.) and their event times >> (i.e., I know whether they have died and when if death occurred prior to >> the >> end of the observation period). Dataset 2 includes another set of people >> for >> which I only have the covariate vector. I would like to use Dataset 1 to >> calibrate either a coxph or survreg model and then use this model to >> determine an "expected time until death" for the individuals in Dataset 2. >> For example, I would like to know when a person in Dataset 2 will die, >> given >> his/ her age and gender. >> >> I checked predict.coxph and predict.survreg as well as the document "A >> Package for Survival Analysis in S" written by Terry M. Therneau but I >> have >> to admit that I'm a bit lost here. > > The first step would be creating a Surv-object, followed by running a > regression that created a coxph-object, using dataset1 as input. So you > should be looking at: > > ?Surv > ?coxph > > There are worked examples in the help pages. You would then run predict() on > the coxph fit with "dataset2" as the newdata argument. The default output is > the linear predictor for the log-hazard relative to a mean survival estimate > but other sorts of estimates are possible. The survfit function provides > survival curve suitable for plotting. > > (You may want to inquire at a local medical school to find statisticians who > have experience with this approach. This is ordinary biostatistics these > days.) > > -- > David. > >> >> Could anyone give me some advice on how this could be done? >> >> Thanks very much in advance, >> >> Michael >> >> >> >> Michael Haenlein >> Professor of Marketing >> ESCP Europe >> Paris, France > > David Winsemius, MD > West Hartford, CT > > ______________________________________________ > 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. > ______________________________________________ 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.
