Regression modelRegression / GLM

Multinomial Logistic Regression

Multinomial logistic regression extends binary logistic regression to outcomes with three or more unordered categories. It models the log-odds of each category relative to a chosen reference category as a linear function of the predictors, and estimates all parameters simultaneously via maximum likelihood. It is the standard choice when the dependent variable is nominal with multiple levels.

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Sources

  1. Agresti, A. (2002). Categorical Data Analysis (2nd ed.). Wiley-Interscience. ISBN: 978-0471360933
  2. Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied Logistic Regression (3rd ed.). Wiley. ISBN: 978-0470582473

Related methods

Referenced by

ScholarGateMultinomial Logistic Regression (Multinomial Logistic Regression). Retrieved 2026-06-04 from https://scholargate.app/en/statistics/multinomial-logistic-regression