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
--
David.
Best regards,
Sebastian
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David Winsemius, MD
West Hartford, CT
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