قارن الطرق

	الانحدار اللوجستي الترتيبي (اللوجيت/البروبيت الترتيبي)	انحدار ذي الحدين السلبي
المجال	الاقتصاد القياسي	الاقتصاد القياسي
العائلة	Regression model	Regression model
سنة النشأة	1980	2011
صاحب الطريقة	McCullagh (proportional odds / cumulative model)	Hilbe (textbook treatment); generalized linear model framework
النوع	Cumulative ordinal regression	Generalized linear model for count data
المصدر التأسيسي	McCullagh, P. (1980). Regression Models for Ordinal Data. Journal of the Royal Statistical Society: Series B, 42(2), 109-142.	Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press.
الأسماء البديلة	ordinal logistic regression, proportional odds model, cumulative logit model, ordered probit	NB regression, NB2 regression, negatif binom regresyonu
ذات صلة	4	4
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.	Negative Binomial Regression is a generalized linear model for count outcomes that extends Poisson regression to handle overdispersion, where the variance of the counts exceeds their mean. Developed in the GLM tradition and treated in depth by Hilbe (2011), it adds a dispersion parameter so that inference stays valid when Poisson would understate the spread of the data.