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Bayesova ordinalna logistička regresija×Ordinarna logistička regresija×
PodručjeStatistikaStatistika
ObiteljRegression modelRegression model
Godina nastanka19991980
TvoracJohnson & Albert (1999); Bayesian proportional odds frameworkPeter McCullagh
VrstaBayesian generalized linear modelOrdinal regression / GLM
Temeljni izvorJohnson, V. E., & Albert, J. H. (1999). Ordinal Data Modeling. Springer. ISBN: 978-0387987484McCullagh, P. (1980). Regression models for ordinal data. Journal of the Royal Statistical Society: Series B (Methodological), 42(2), 109–142. DOI ↗
Drugi naziviBayesian proportional odds model, Bayesian cumulative logit model, Bayesian ordered logit, Bayesian cumulative link modelproportional-odds model, cumulative link model, ordered logit, OLR
Srodne66
SažetakBayesian ordinal logistic regression extends the classical proportional odds model by placing prior distributions on the regression coefficients and threshold parameters and updating them with observed data via Bayes' theorem. The result is a full posterior distribution over all parameters, enabling uncertainty quantification without relying on large-sample approximations.Ordinal 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.
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ScholarGateUsporedite metode: Bayesian Ordinal Logistic Regression · Ordinal Logistic Regression. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare