R-help list and interested parties, On Cross Validated mpiktas correctly noted that both the I() and rms Glm/Predict solution produce incorrect results (http://stats.stackexchange.com/questions/6684/how-can-one-use-the-predict-function-on-a-lm-object-where-the-ivs-have-been-dynam/6718#6718). As far as I can tell, the short version is that both I and rms leave scale() in the formula for the lm object, so predict and Predict() run scale on the provided newdata prior to generating the actual prediction. So, for now, there appears no easy way to do this the way I hoped. Time for me to get down to writing functions.
Best, Russell S. Pierce, M.A. Visual Cognition Lab Department of Psychology University of California, Riverside 900 University Avenue Riverside, CA 92521 Lab Phone: (951) 827-7399 On Sat, Jan 29, 2011 at 9:12 AM, Russell Pierce <rpier...@ucr.edu> wrote: > Just in case someone else stumbles onto this thread and is facing a > similar issue: The quick solution for me turned out to be using Glm > and Predict in the rms package. Thanks go to Joshua and Ista for > helping me out with this issue. Double thanks go to Joshua for > suggesting I take a closer look at the rms package. > > library(rms) > dat <- data.frame(xxA = rnorm(20,10), xxB = rnorm(20,20)) > dat$out <- with(dat,xxA+xxB+xxA*xxB+rnorm(20,20)) > rms.res <- Glm(out ~ scale(xxA)*scale(xxB),data=dat) > newdata <- as.data.frame(Predict(rms.res,xxA=c(-1,0,1),xxB=c(-1,0,1))[,1:3]) > > ----------------------------------- > Russell S. Pierce, M.A. > Visual Cognition Lab > Department of Psychology > University of California, Riverside > 900 University Avenue > Riverside, CA 92521 > Lab Phone: (951) 827-7399 > ______________________________________________ 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.
