Method evidence record
Bayesian Ordinal Logistic Regression
Bayesian 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.
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Bayesian Ordinal Logistic Regression (Proportional Odds Model)
Taxonomic method record · regression-model / statistics
- Johnson, V. E., & Albert, J. H. (1999). Ordinal Data Modeling. Springer. · ISBN 978-0387987484
- Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. · ISBN 978-1439840955
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