Dear List:
Below is the validation output of a fitted ordinal logistic model
using the bootstrap in the rms package. My interpretation is that
most of the corrected indices indicate little overfitting, however the
slope seems to indicate that the model is too optimistic. Given that
most of the corrected indices seem reasonable, would it be appropriate
to use this model on future data if the corrected intercept and slope
estimates are used?
index.orig training test optimism index.corrected n
Dxy 0.9932 0.9940 0.9905 0.0035 0.9897 363
R2 0.9291 0.9364 0.9163 0.0202 0.9089 363
Intercept 0.0000 0.0000 0.0233 -0.0233 0.0233 363
Slope 1.0000 1.0000 0.7836 0.2164 0.7836 363
Emax 0.0000 0.0000 0.0582 0.0582 0.0582 363
D 0.9118 0.9190 0.8915 0.0275 0.8844 363
U -0.0110 -0.0110 0.0124 -0.0234 0.0124 363
Q 0.9228 0.9299 0.8791 0.0508 0.8720 363
B 0.0205 0.0172 0.0239 -0.0067 0.0272 363
Any input is much appreciated.
Thanks,
Adam
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