Timeline for Maximum number of categorical predictors in multinomial (polytomous) logistic regression
Current License: CC BY-SA 3.0
5 events
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| Mar 9, 2018 at 19:31 | comment | added | blokeman | Nope, never heard about such a thing in my life :) Anyway, thanks a lot for your clarifications and input. | |
| Mar 9, 2018 at 19:08 | comment | added | AdamO | @blokeman Thanks for reporting the results of your investigation. I would agree that, if my hand were forced to settle on merely one approach to the problem, I would prefer H&L over Peduzzi. But neither is sufficient to explain the problem. Out of curiosity, did you calculate the retrospective power of your analysis (akin to using a parametric bootstrap)? | |
| Mar 9, 2018 at 19:06 | comment | added | blokeman | I did as you suggest. In a boostrap analysis with 1000 iterations, the only coefficients with serious instability are ones pertaining to predictor categories with low or zero event counts for one or other response category. This would seem to support H&L's view that in the case of categorical covariates, having enough events in all predictor categories is more relevant than events per parameter. | |
| Mar 6, 2018 at 15:15 | history | edited | AdamO | CC BY-SA 3.0 |
added 220 characters in body
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| Mar 5, 2018 at 21:51 | history | answered | AdamO | CC BY-SA 3.0 |