pema: Penalized Meta-Analysis

Conduct penalized meta-analysis, see Van Lissa, Van Erp, & Clapper (2023) <doi:10.31234/osf.io/6phs5>. In meta-analysis, there are often between-study differences. These can be coded as moderator variables, and controlled for using meta-regression. However, if the number of moderators is large relative to the number of studies, such an analysis may be overfit. Penalized meta-regression is useful in these cases, because it shrinks the regression slopes of irrelevant moderators towards zero.

Version:	0.1.3
Depends:	R (≥ 3.4.0)
Imports:	methods, rstan (≥ 2.18.1), Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstantools (≥ 2.1.1), sn, shiny, ggplot2
LinkingTo:	BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Suggests:	rmarkdown, knitr, mice, testthat (≥ 3.0.0)
Published:	2023-03-16
DOI:	10.32614/CRAN.package.pema
Author:	Caspar J van Lissa [aut, cre], Sara J van Erp [aut]
Maintainer:	Caspar J van Lissa <c.j.vanlissa at tilburguniversity.edu>
License:	GPL (≥ 3)
URL:	https://github.com/cjvanlissa/pema
NeedsCompilation:	yes
SystemRequirements:	GNU make
Citation:	pema citation info
Materials:	README
In views:	MetaAnalysis
CRAN checks:	pema results

Documentation:

Reference manual:	pema.pdf
Vignettes:	Conducting a Bayesian Regularized Meta-analysis

Downloads:

Package source:	pema_0.1.3.tar.gz
Windows binaries:	r-devel: pema_0.1.3.zip, r-release: pema_0.1.3.zip, r-oldrel: pema_0.1.3.zip
macOS binaries:	r-release (arm64): pema_0.1.3.tgz, r-oldrel (arm64): pema_0.1.3.tgz, r-release (x86_64): pema_0.1.3.tgz, r-oldrel (x86_64): pema_0.1.3.tgz
Old sources:	pema archive

Linking:

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