Journal of Data Science and Modeling

Bayesian Nonparametric Bivariate Meta Analysis

Document Type : Research Manuscript

Author

Ehsan Ormoz

Department of Mathematics and Statistics, Mashhad Branch, Islamic Azad University

https://doi.org/10.22054/jcsm.2018.36484.1013
Abstract
In the meta-analysis of clinical trials, usually the data of each trail summarized by one or more outcome measure estimates which reported along with their standard errors. In the case that summary data are multi-dimensional, usually, the data analysis will be performed in the form of a number of separated univariate analysis. In such a case the correlation between summary statistics would be ignored. In contrast, a multivariate meta-analysis model, use from these correlations synthesizes the outcomes, jointly to estimate the multiple pooled effects simultaneously. In this paper, we present a nonparametric Bayesian bivariate random effect meta-analysis.

Keywords

Bayesian Nonparametric
Gibbs algorithm
Meta-analysis
Bivariate Distribution
Bayesian Model Selection
Subjects
Journal of Data Science and Modeling
Volume 1, Issue 1 - Serial Number 1
December 2022
Pages 129-141

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