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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 ORCID iD [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:

Please use the canonical form https://CRAN.R-project.org/package=pema to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.