metapack: Bayesian Meta-Analysis and Network Meta-Analysis

Contains functions performing Bayesian inference for meta-analytic and network meta-analytic models through Markov chain Monte Carlo algorithm. Currently, the package implements Yao, Kim, Chen, Ibrahim, Shah, and Jianxin Lin (2015) <doi:10.1080/01621459.2015.1006065> and network meta-regression models using heavy-tailed multivariate random effects with covariate-dependent variances. For maximal computational efficiency, the Markov chain Monte Carlo samplers for each model, written in C++, are fine-tuned. This software has been developed under the auspices of the National Institutes of Health and Merck & Co., Inc., Kenilworth, NJ, USA.

Version: 0.1.1
Depends: R (≥ 3.4)
Imports: Rcpp, ggplot2, methods, gridExtra
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, BH
Suggests: knitr, rmarkdown
Published: 2021-02-23
Author: Daeyoung Lim [aut, cre], Ming-Hui Chen [ctb], Sungduk Kim [ctb], Joseph Ibrahim [ctb], Arvind Shah [ctb], Jianxin Lin [ctb]
Maintainer: Daeyoung Lim <daeyoung.lim at uconn.edu>
BugReports: https://github.com/daeyounglim/metapack/issues
License: GPL (≥ 3)
URL: http://merlot.stat.uconn.edu/packages/metapack/
NeedsCompilation: yes
Citation: metapack citation info
Materials: README NEWS
CRAN checks: metapack results

Downloads:

Reference manual: metapack.pdf
Vignettes: Introduction to metapack
Package source: metapack_0.1.1.tar.gz
Windows binaries: r-devel: metapack_0.1.1.zip, r-release: metapack_0.1.1.zip, r-oldrel: metapack_0.1.1.zip
macOS binaries: r-release: metapack_0.1.1.tgz, r-oldrel: metapack_0.1.1.tgz
Old sources: metapack archive

Linking:

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