For this case B=200 should work well if using the bootstrap. For cross-val. you can use B=10-fold cross-val and repeat the process 100 times for adequate precision, averaging over the 100 as done in http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/logistic.val.pdf (note this was using the Design package and there may be subtle changes with the rms package).
Frank viostorm wrote: > > I have a logistic regression model I'm trying to do k-fold cross > validation on. > > The number of observations is approximately 550 and an event rate of about > 30% > > Does anyone have a recommendation for a B value to use for this data set? > -----Frank Harrell Department of Biostatistics, Vanderbilt University-- View this message in context: http://r.789695.n4.nabble.com/recommendation-on-B-for-validate-lrm-tp3486200p3488384.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.
