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.

Paroli, R., Consonni, G., Objective Bayesian Comparison of Order-Constrained Models in Contingency Tables., <<TEST>>, 2020; 2020 (29): 139-165. [doi:10.1007/s11749-019-00650-w] [http://hdl.handle.net/10807/133659]

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

Paroli, Roberta
Primo
;
Consonni, Guido
Secondo
2019

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.
Inglese
Paroli, R., Consonni, G., Objective Bayesian Comparison of Order-Constrained Models in Contingency Tables., <<TEST>>, 2020; 2020 (29): 139-165. [doi:10.1007/s11749-019-00650-w] [http://hdl.handle.net/10807/133659]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/133659
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