The explanation is in the first paragraph of the help file for the summary.rms function [inter-quartile-range odds ratios, which handles nonlinearities]. Note that you are assuming that age has a linear effect, which is counterintuitive. Frank
Sebastian Pölsterl wrote > > Hi, > > I'm using the rms package to do regression analysis using the lrm > function. Retrieving odds ratios is possible using summary.rms. However, > I could not find any information on how exactly the odds ratios for > continuous variables are calculated. It doesn't appear to be the odds > ratio at 1 unit increase, because the output of summary.rms did not > match the coefficient's value. > > E.g. print gives me: > > Coef S.E. Wald Z Pr(>|Z|) > age 0.1166 0.0289 4.04 <0.0001 > > whereas summary gives me: > > Factor Low High Diff. Effect S.E. Lower 0.95 Upper 0.95 > age 27.0000 37.00000 10.0000 0.78 0.20 0.40 1.17 > Odds Ratio 27.0000 37.00000 10.0000 2.19 NA 1.49 3.22 > > Does anybody know how these values are obtained, especially in the > presence of interactions? > > Best regards, > Sebastian > > ______________________________________________ > R-help@ 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/Odds-Ratios-in-rms-package-tp4634004p4634033.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.