Objective Bayesian Comparison of Order-Constrained Models in Contingency Tables.

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Abstract

In social and biomedical sciences, testing in contingency tables often involves order restrictions on cell probabilities parameters. We develop objective Bayes methods for order-constrained testing and model comparison when observations arise under product binomial or multinomial sampling. Specifically, we consider tests for monotone order of the parameters against equality of all parameters. Our strategy combines in a unified way both the intrinsic prior methodology and the encompassing prior approach in order to compute Bayes factors and posterior model probabilities. Performance of our method is evaluated on several simulation studies and real datasets.
Lingua originaleEnglish
pagine (da-a)139-165
Numero di pagine27
RivistaTEST
Volume2020
DOI
Stato di pubblicazionePubblicato - 2019

Keywords

  • Bayes factor
  • Contingency table
  • Encompassing prior
  • Intrinsic prior
  • Order constraint
  • Product binomial model

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