Multinomial logistic regression: Difference between revisions

Revision as of 05:37, 1 May 2019

Revision as of 14:42, 10 August 2019

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===As a set of independent binary regressions===

One fairly simple way toTo arrive at the multinomial logit model, isone tocan imagine, for ''K'' possible outcomes, running ''K''-1 independent binary logistic regression models, in which one outcome is chosen as a "pivot" and then the other ''K''-1 outcomes are separately regressed against the pivot outcome. This would proceed as follows, if outcome ''K'' (the last outcome) is chosen as the pivot:

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