Replace the soon-to-be Design with rms. Specify surv=TRUE to cph so that approximate rather than fully correct standard errors will be computed by survplot/survest. Frank
christopher.a.hane wrote: > > Hi, > > I have a Cox PH model that's large for my server, 120K rows, ~300 factors > with 3 levels each, so about 1000 columns. The 300 factors all pass a > preliminary test of association with the outcome. Solving this with cph > from > Design takes about 3 hours. I have created the fit with x=T, y=T to save > the > model data. > > I want to validate the PH assumption by calling survplot(fit, gender=NA, > logt=TRUE, loglog=TRUE) for many of the factors (here gender is one column > name). Just creating this one plot takes 40m. > > I'd be happy to sample from the fitted model to create these tests, or > figure out another way to check assumptions in the model. > > Has anyone done something similar, or have other suggestions for tests > that > scale better? > > thanks. > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Design-Survplot-performance-tp3684580p3684626.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.
