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Objective Bayesian comparison of order-constrained models in contingency tables

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Listed:
  • Roberta Paroli

    (Università Cattolica del Sacro Cuore)

  • Guido Consonni

    (Università Cattolica del Sacro Cuore)

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.

Suggested Citation

  • Roberta Paroli & Guido Consonni, 2020. "Objective Bayesian comparison of order-constrained models in contingency tables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 139-165, March.
    • Handle: RePEc:spr:testjl:v:29:y:2020:i:1:d:10.1007_s11749-019-00650-w
    DOI: 10.1007/s11749-019-00650-w
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    References listed on IDEAS

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    1. Consonni, Guido & La Rocca, Luca, 2008. "Tests Based on Intrinsic Priors for the Equality of Two Correlated Proportions," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1260-1269.
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