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BayesMultMeta  

Bayesian Multivariate Meta-Analysis
View on CRAN: Click here


Download and install BayesMultMeta package within the R console
Install from CRAN:
install.packages("BayesMultMeta")

Install from Github:
library("remotes")
install_github("cran/BayesMultMeta")

Install by package version:
library("remotes")
install_version("BayesMultMeta", "0.1.1")



Attach the package and use:
library("BayesMultMeta")
Maintained by
Erik Thorsén
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-17
Latest Update: 2022-06-09
Description:
Objective Bayesian inference procedures for the parameters of the multivariate random effects model with application to multivariate meta-analysis. The posterior for the model parameters, namely the overall mean vector and the between-study covariance matrix, are assessed by constructing Markov chains based on the Metropolis-Hastings algorithms as developed in Bodnar and Bodnar (2021) (). The Metropolis-Hastings algorithm is designed under the assumption of the normal distribution and the t-distribution when the Berger and Bernardo reference prior and the Jeffreys prior are assigned to the model parameters. Convergence properties of the generated Markov chains are investigated by the rank plots and the split hat-R estimate based on the rank normalization, which are proposed in Vehtari et al. (2021) ().
How to cite:
Erik Thorsén (2022). BayesMultMeta: Bayesian Multivariate Meta-Analysis. R package version 0.1.1, https://cran.r-project.org/web/packages/BayesMultMeta. Accessed 06 Jun. 2026.
Previous versions and publish date:
0.1.0 (2022-05-17 18:50)
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Complete documentation for BayesMultMeta
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