Review Articles

Objective Bayesian hypothesis testing and estimation for the intraclass model

Duo Zhang ,

Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, USA

Daojiang He ,

School of Mathematics and Computer Science, Anhui Normal University, Wuhu, People's Republic of China

Xiaoqian Sun ,

Department of Mathematical Sciences, Clemson University, Clemson, SC, USA

Min Wang

Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX, USA

Pages 37-47 | Received 06 Nov. 2017, Accepted 24 May. 2018, Published online: 07 Jun. 2018,
  • Abstract
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The intraclass correlation coefficient (ICC) plays an important role in various fields of study as a coefficient of reliability. In this paper, we consider objective Bayesian analysis for the ICC in the context of normal linear regression model. We first derive two objective priors for the unknown parameters and show that both result in proper posterior distributions. Within a Bayesian decision-theoretic framework, we then propose an objective Bayesian solution to the problems of hypothesis testing and point estimation of the ICC based on a combined use of the intrinsic discrepancy loss function and objective priors. The proposed solution has an appealing invariance property under one-to-one reparametrisation of the quantity of interest. Simulation studies are conducted to investigate the performance the proposed solution. Finally, a real data application is provided for illustrative purposes.


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