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Ordinálna logistická regresia×Model probitovej regresie×
OdborŠtatistikaEkonometria
RodinaRegression modelRegression model
Rok vzniku19802018
TvorcaPeter McCullaghGreene (textbook treatment); classical discrete-choice modelling
TypOrdinal regression / GLMBinary discrete-choice model
Pôvodný zdrojMcCullagh, P. (1980). Regression models for ordinal data. Journal of the Royal Statistical Society: Series B (Methodological), 42(2), 109–142. DOI ↗Greene, W. H. (2018). Econometric Analysis (8th ed.). Pearson. ISBN: 978-0134461366
Ďalšie názvyproportional-odds model, cumulative link model, ordered logit, OLRprobit regression, normit model, Probit Modeli
Príbuzné65
ZhrnutieOrdinal 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 probit model is a regression method for a binary (0/1) outcome that maps a linear index of the predictors through the standard normal cumulative distribution function to produce a probability. It is a classical discrete-choice alternative to logistic regression, developed in standard econometrics treatments such as Greene's Econometric Analysis (2018).
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ScholarGatePorovnať metódy: Ordinal Logistic Regression · Probit Model. Získané 2026-06-17 z https://scholargate.app/sk/compare