Thanks a lot David, I must have missed this sentence. Best regards, Sebastian
Am 20.06.2012 21:05, schrieb David Winsemius: > > On Jun 20, 2012, at 12:12 PM, 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? > > It is explained in the first paragraph of ?summary.rms, : > > " By default, inter-quartile range effects (odds ratios, hazards ratios, > etc.) are printed for continuous factors," > > ... and the labeling makes it fairly clear (at least it was for me) > that it is an odds ratio for a change in predictor value from the 25th > to the 75th percentile (which are the values in the Low and High columns) > > In the presence of interactions you should not be looking at the > coefficients, but rather at the predictions. > > ?Predict > ______________________________________________ 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.
