An Empirical Bayes Method for Multivariate Meta-analysis with an Application in Clinical Trials.

Published

Journal Article

We propose an empirical Bayes method for evaluating overall and study-specific treatment effects in multivariate meta-analysis with binary outcome. Instead of modeling transformed proportions or risks via commonly used multivariate general or generalized linear models, we directly model the risks without any transformation. The exact posterior distribution of the study-specific relative risk is derived. The hyperparameters in the posterior distribution can be inferred through an empirical Bayes procedure. As our method does not rely on the choice of transformation, it provides a flexible alternative to the existing methods and in addition, the correlation parameter can be intuitively interpreted as the correlation coefficient between risks.

Full Text

Duke Authors

Cited Authors

  • Chen, Y; Luo, S; Chu, H; Su, X; Nie, L

Published Date

  • July 29, 2014

Published In

Volume / Issue

  • 43 / 16

Start / End Page

  • 3536 - 3551

PubMed ID

  • 25089070

Pubmed Central ID

  • 25089070

International Standard Serial Number (ISSN)

  • 0361-0926

Digital Object Identifier (DOI)

  • 10.1080/03610926.2012.700379

Language

  • eng

Conference Location

  • United States