Interpreting multinomial logistic regression

Abstract

Social and biological scientists widely use logit (logistic) regression to model binary dependent variables such as move/stay or live/die. Techniques for modeling multiple-category dependent variables are a relatively recent development, however. Asking Stata to perform multinomial logistic regression is easy; given a Y with three or more unordered categories, predicted by X1 and X2, you type ‘mlogit Y X1 X2’. If Y has only two categories, mlogit fits the same model as logit or logistic. Otherwise, though, an mlogit model is more complex. This insert, a sort of “beginners guide to multinomial logit” written while stormbound at the Nullagvik Hotel, illustrates several ways to interpret mlogit output.

Department

Sociology

Publication Date

5-1-1993

Journal Title

Stata Technical Bulletin

Publisher

Stata Corporation

Document Type

Article

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