|Title||An Empirical Bayes Method for Multivariate Meta-analysis with an Application in Clinical Trials.|
|Publication Type||Journal Article|
|Year of Publication||2014|
|Authors||Chen, Yong, Sheng Luo, Haitao Chu, Xiao Su, and Lei Nie|
|Journal||Commun Stat Theory Methods|
|Date Published||2014 Jul 29|
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.
|Alternate Journal||Commun Stat Theory Methods|
|Original Publication||An empirical bayes method for multivariate meta-analysis with an application in clinical trials.|
|PubMed Central ID||PMC4115294|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R03 HS020666 / HS / AHRQ HHS / United States
U01 NS043127 / NS / NINDS NIH HHS / United States
U01 NS043128 / NS / NINDS NIH HHS / United States
An Empirical Bayes Method for Multivariate Meta-analysis with an Application in Clinical Trials.