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الانحدار اللوجستي الترتيبي×الانحدار اللوجستي متعدد الحدود×
المجالالإحصاءالإحصاء
العائلةRegression modelRegression model
سنة النشأة19801966–1974
صاحب الطريقةPeter McCullaghCox (1966); Theil (1969); formalized by McFadden (1974)
النوعOrdinal regression / GLMGeneralized linear model
المصدر التأسيسيMcCullagh, P. (1980). Regression models for ordinal data. Journal of the Royal Statistical Society: Series B (Methodological), 42(2), 109–142. DOI ↗Agresti, A. (2002). Categorical Data Analysis (2nd ed.). Wiley-Interscience. ISBN: 978-0471360933
الأسماء البديلةproportional-odds model, cumulative link model, ordered logit, OLRpolytomous logistic regression, softmax regression, multinomial logit, nominal logistic regression
ذات صلة64
الملخصOrdinal logistic regression — most commonly the proportional-odds model — estimates the relationship between one or more predictors and an ordered categorical outcome (e.g., Likert scales, disease severity grades, educational attainment levels). It models cumulative log-odds across the ordered categories while assuming a single shared effect of each predictor at all thresholds.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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ScholarGateقارن الطرق: Ordinal Logistic Regression · Multinomial Logistic Regression. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare