ScholarGate
Assistent

Compara mètodes

Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.

Regressió logística ordinal (model de probabilitats proporcionals)×Multinomial Logistic Regression×
CampEstadísticaEstadística
FamíliaRegression modelRegression model
Any d'origen20101966–1974
Autor originalAgresti (textbook treatment); proportional odds modelCox (1966); Theil (1969); formalized by McFadden (1974)
TipusOrdinal logistic regressionGeneralized linear model
Font seminalAgresti, A. (2010). Analysis of Ordinal Categorical Data (2nd ed.). Wiley. DOI ↗Agresti, A. (2002). Categorical Data Analysis (2nd ed.). Wiley-Interscience. ISBN: 978-0471360933
Àliesproportional odds model, ordered logit, ordinal logistic regression, Ordinal Regresyon (Proportional Odds)polytomous logistic regression, softmax regression, multinomial logit, nominal logistic regression
Relacionats54
ResumOrdinal logistic regression models an ordered categorical outcome — such as a Likert rating, a satisfaction level, or an education tier — as a function of predictors. It is the ordinal extension of logistic regression, developed in standard treatments such as Agresti's Analysis of Ordinal Categorical Data (2010), and in its most common form it is the proportional odds model.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.
ScholarGateConjunt de dades
  1. v1
  2. 2 Fonts
  3. PUBLISHED
  1. v1
  2. 2 Fonts
  3. PUBLISHED

Ves a la cerca Baixa les diapositives

ScholarGateCompara mètodes: Ordinal Regression · Multinomial Logistic Regression. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare