Multinomial Logistic Regression

Chanyeong Kwak; Alan Clayton-Matthews

doi:10.1097/00006199-200211000-00009

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JOURNAL ARTICLE

Multinomial Logistic Regression

Chanyeong Kwak Alan Clayton-Matthews

Year: 2002 Journal: Nursing Research Vol: 51 (6)Pages: 404-410 Publisher: Lippincott Williams & Wilkins

DOI: 10.1097/00006199-200211000-00009

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Abstract

This method can handle situations with several categories. There is no need to limit the analysis to pairs of categories, or to collapse the categories into two mutually exclusive groups so that the (more familiar) logit model can be used. Indeed, any strategy that eliminates observations or combines categories only leads to less efficient estimates.

Keywords:

Multinomial probit Multinomial logistic regression Econometrics Ordered probit Estimator Independence of irrelevant alternatives Statistics Independence (probability theory) Logistic regression Logit Multinomial distribution Mathematics Probit Variable (mathematics) Variables

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Energy Efficiency and Management

Physical Sciences → Energy → Renewable Energy, Sustainability and the Environment

Forecasting Techniques and Applications

Social Sciences → Decision Sciences → Management Science and Operations Research

Advanced Statistical Process Monitoring

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

Multinomial Logistic Regression

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