قارن الطرق

	الانحدار اللوجستي الترتيبي (اللوجيت/البروبيت الترتيبي)	الانحدار اللوجستي	الانحدار اللوجستي متعدد الحدود
المجال	الاقتصاد القياسي	إحصاء البحث	الاقتصاد القياسي
العائلة	Regression model	Process / pipeline	Regression model
سنة النشأة	1980	1958	1974
صاحب الطريقة	McCullagh (proportional odds / cumulative model)	David Roxbee Cox	McFadden
النوع	Cumulative ordinal regression	Method	Multinomial logistic regression
المصدر التأسيسي	McCullagh, P. (1980). Regression Models for Ordinal Data. Journal of the Royal Statistical Society: Series B, 42(2), 109-142.	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.	McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503
الأسماء البديلة	ordinal logistic regression, proportional odds model, cumulative logit model, ordered probit	logit model, binomial logistic regression, LR	multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon
ذات صلة	4	3	5
الملخص	Ordered logit is a cumulative regression model for an ordinal dependent variable, fitting a logit (or probit) link to the cumulative category probabilities. Developed in McCullagh's 1980 treatment of regression models for ordinal data, it is the standard tool for Likert-scale, rating, and ranked outcomes.	Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.	Multinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category.