Timeline for Multinomial Logistic Regression- goodness of fit and alternatives
Current License: CC BY-SA 3.0
5 events
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| Apr 3, 2018 at 11:27 | comment | added | mkt | I agree with @Berkan and don't think multinomial regression is ideal here (among other things, your discretized variable is now ordinal, not categorical). But as for your question #3, the model cannot 'take care of' interaction effects if they have not been specified in its structure. | |
| Apr 3, 2018 at 11:12 | history | edited | kjetil b halvorsen♦ | CC BY-SA 3.0 |
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| Dec 29, 2015 at 9:34 | comment | added | Tapan Khopkar | Thanks @Zhubarb for the quick revert. I had already gone through the earlier question, and one of my team members is pursuing the linear model. However, on the multinomial logistic model, I would still like to have answers to the questions 3 & 4 from my list above. Also, Would be great if someone could Someone could point me to R-implementations for: Hausman or Small-Hsiao tests of the IIA Various scalar measures of fit (like McFadden's R2) Wald or LR tests for combining alternatives | |
| Dec 29, 2015 at 9:23 | comment | added | Zhubarb | This question has been asked on the website previously. Here is one of the links: stats.stackexchange.com/questions/83899/…. Translating a regression problem (by its nature) to classification just because regression does not give good results is not a very sound strategy. If I were you, I would spend more time on identifying why regression did not turn out as well as expected, rather than switching to classification. | |
| Dec 29, 2015 at 9:18 | history | asked | Tapan Khopkar | CC BY-SA 3.0 |