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Bayes Factor Consistency for One-way Random Effects Model

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  • Min Wang
  • Xiaoqian Sun

Abstract

In this article, we consider Bayesian hypothesis testing for the balanced one-way random effects model. A special choice of the prior formulation for the ratio of variance components is shown to yield an explicit closed-form Bayes factor without integral representation. Furthermore, we study the consistency issue of the resulting Bayes factor under three asymptotic scenarios: either the number of units goes to infinity, the number of observations per unit goes to infinity, or both go to infinity. Finally, the behavior of the proposed approach is illustrated by simulation studies.

Suggested Citation

  • Min Wang & Xiaoqian Sun, 2014. "Bayes Factor Consistency for One-way Random Effects Model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(23), pages 5072-5090, December.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:23:p:5072-5090
    DOI: 10.1080/03610926.2012.739252
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    Cited by:

    1. Kang, Shuaimin & Wang, Min & Lu, Tao, 2015. "On the consistency of the objective Bayes factor for the integral priors in the one-way random effects model," Statistics & Probability Letters, Elsevier, vol. 103(C), pages 17-23.
    2. Min Wang & Guangying Liu, 2016. "A Simple Two-Sample Bayesian t -Test for Hypothesis Testing," The American Statistician, Taylor & Francis Journals, vol. 70(2), pages 195-201, May.

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