A hybrid approximation bayesian test of variance components for longitudinal data

研究成果: Article

1 引文 斯高帕斯(Scopus)

摘要

The test of variance components of possibly correlated random effects in generalized linear mixed models (GLMMs) can be used to examine if there exists heterogeneous effects. The Bayesian test with Bayes factors offers a flexible method. In this article, we focus on the performance of Bayesian tests under three reference priors and a conjugate prior: an approximate uniform shrinkage prior, modified approximate Jeffreys' prior, half-normal unit information prior and Wishart prior. To compute Bayes factors, we propose a hybrid approximation approach combining a simulated version of Laplace's method and importance sampling techniques to test the variance components in GLMMs.

原文English
頁(從 - 到)2849-2864
頁數16
期刊Communications in Statistics - Theory and Methods
39
發行號16
DOIs
出版狀態Published - 2010 八月 19

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

指紋 深入研究「A hybrid approximation bayesian test of variance components for longitudinal data」主題。共同形成了獨特的指紋。

  • 引用此