विधियों की तुलना करें

	क्रमिक लॉजिस्टिक रिग्रेशन	सामान्यीकृत रेखीय मॉडल (GLM)
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Regression model
उद्भव वर्ष	1980	1972
प्रवर्तक	Peter McCullagh	John A. Nelder & Robert W. M. Wedderburn
प्रकार	Ordinal regression / GLM	Regression framework
मौलिक स्रोत	McCullagh, P. (1980). Regression models for ordinal data. Journal of the Royal Statistical Society: Series B (Methodological), 42(2), 109–142.	Nelder, J. A., & Wedderburn, R. W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society: Series A (General), 135(3), 370–384.
उपनाम	proportional-odds model, cumulative link model, ordered logit, OLR	GLM, generalized regression, exponential family regression, link-function model
संबंधित	6	6
सारांश	Ordinal 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.	The Generalized Linear Model is a unified regression framework that extends ordinary linear regression to outcomes from the exponential family — including binary, count, proportion, and continuous positive outcomes. A link function connects the linear predictor to the mean of the response, enabling principled modelling beyond the Gaussian case.