[R] Odds Ratios in rms package

[Sebastian Pölsterl]

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
>