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Uređena logistička regresija (uređeni logit/probit)×Logistička regresija×
PodručjeEkonometrijaIstraživačka statistika
ObiteljRegression modelProcess / pipeline
Godina nastanka19801958
TvoracMcCullagh (proportional odds / cumulative model)David Roxbee Cox
VrstaCumulative ordinal regressionMethod
Temeljni izvorMcCullagh, P. (1980). Regression Models for Ordinal Data. Journal of the Royal Statistical Society: Series B, 42(2), 109-142. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
Drugi naziviordinal logistic regression, proportional odds model, cumulative logit model, ordered probitlogit model, binomial logistic regression, LR
Srodne43
SažetakOrdered 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.
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ScholarGateUsporedite metode: Ordered Logit · Logistic Regression. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare