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الانحدار اللوجستي الترتيبي×انحدار المربعات الصغرى العادية (OLS)×
المجالالإحصاءالاقتصاد القياسي
العائلةRegression modelRegression model
سنة النشأة19802019
صاحب الطريقةPeter McCullaghWooldridge (textbook treatment); classical least squares
النوعOrdinal regression / GLMLinear regression
المصدر التأسيسيMcCullagh, P. (1980). Regression models for ordinal data. Journal of the Royal Statistical Society: Series B (Methodological), 42(2), 109–142. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
الأسماء البديلةproportional-odds model, cumulative link model, ordered logit, OLRordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
ذات صلة65
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.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
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ScholarGateقارن الطرق: Ordinal Logistic Regression · OLS Regression. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare