For something like this the best (and possibly only reasonable) option is to use simulation. I have posted on the general steps for using simulation for power studies in this list and elsewhere before, but probably never with coxph.
The general steps still hold, but the complicated part here will be to simulate the data. I would recommend something along the lines of: 1. generate a value for the censoring time, possibly exponential or weibull (for simplicity I would make this not dependent on the covariates if reasonable). 2. generate a value for the covariate for the given time period (sample function possibly), then generate a survival time for this covariate value (possibly weibull distribution, or lognormal, exponential, etc.) If the survival time is less than the time period and censoring time then you have an event and a time to the event. If the survival time is longer than the censoring time, but not longer than the time period (for the covariate), then you have censoring and you can record the time to censoring. If the survival time is longer than the time period then you have the row information for that time period and can move on to the next time period where you will first randomly choose the covariate value again, then generate another survival time based on the covariate and given that they have already survived a given amount. Continue with this until you have an event or censoring time for each subject. On Fri, Jul 13, 2012 at 9:17 AM, Paul Miller <pjmiller...@yahoo.com> wrote: > Hello All, > > Does anyone know where I can find information about how to do a power > analysis for Cox regression with a time-varying covariate using R or some > other readily available software? I've done some searching online but haven't > found anything. > > Thanks, > > Paul > > ______________________________________________ > 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. -- Gregory (Greg) L. Snow Ph.D. 538...@gmail.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.