Objective Bayesian comparison of order-constrained models in contingency tables

Roberta Paroli () and Guido Consonni ()
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Roberta Paroli: Università Cattolica del Sacro Cuore
Guido Consonni: Università Cattolica del Sacro Cuore

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2020, vol. 29, issue 1, No 8, 139-165

Abstract: 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.

Keywords: Bayes factor; Contingency table; Encompassing prior; Intrinsic prior; Order constraint; Product binomial model; 62F15; 62H17; 62P10; 62P15 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11749-019-00650-w

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