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Ordinalna logistička regresija×Kvantilna regresija×
OblastStatistikaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka19801978
TvoracPeter McCullaghKoenker & Bassett
TipOrdinal regression / GLMConditional quantile regression
Temeljni izvorMcCullagh, P. (1980). Regression models for ordinal data. Journal of the Royal Statistical Society: Series B (Methodological), 42(2), 109–142. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Drugi naziviproportional-odds model, cumulative link model, ordered logit, OLRconditional quantile regression, regression quantiles, Kantil Regresyon
Srodne65
SažetakOrdinal 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.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGateUporedite metode: Ordinal Logistic Regression · Quantile Regression. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare