Package: metapack
Type: Package
Title: Bayesian Meta-Analysis and Network Meta-Analysis
Version: 0.3
Date: 2024-01-14
Authors@R: c(
	person("Daeyoung", "Lim", email = "Daeyoung.Lim@fda.hhs.gov",
	role = c("aut", "cre")),
	person("Ming-Hui", "Chen", email = "ming-hui.chen@uconn.edu",
	role = "ctb"),
	person("Sungduk", "Kim", email = "kims2@mail.nih.gov",
	role = "ctb"),
	person("Joseph", "Ibrahim", email = "ibrahim@bios.unc.edu",
	role = "ctb"),
	person("Arvind", "Shah", email = "arvind_shah@merck.com", role = "ctb"),
	person("Jianxin", "Lin", email = "jianxin_lin@merck.com", role = "ctb"))
Description: Contains functions performing Bayesian inference for meta-analytic and network meta-analytic models through Markov chain Monte Carlo algorithm. Currently, the package implements Hui Yao, Sungduk Kim, Ming-Hui Chen, Joseph G. Ibrahim, Arvind K. Shah, and Jianxin Lin (2015) <doi:10.1080/01621459.2015.1006065> and Hao Li, Daeyoung Lim, Ming-Hui Chen, Joseph G. Ibrahim, Sungduk Kim, Arvind K. Shah, Jianxin Lin (2021) <doi:10.1002/sim.8983>. 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.
License: GPL (>= 3)
Encoding: UTF-8
LazyLoad: yes
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: yes
Imports: Rcpp, ggplot2, methods, gridExtra, Formula
Depends: R (>= 3.4)
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, BH
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://events.stat.uconn.edu/metapack/
BugReports: https://github.com/daeyounglim/metapack/issues
Packaged: 2024-01-23 17:06:22 UTC; daeyounglim
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@fda.hhs.gov>
Repository: CRAN
Date/Publication: 2024-01-24 17:10:02 UTC
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