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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "pema" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'pema: Penalized Meta-Analysis'
version: 0.1.5
doi: 10.31234/osf.io/6phs5
identifiers:
- type: doi
  value: 10.32614/CRAN.package.pema
abstract: Conduct penalized meta-analysis, see Van Lissa, Van Erp, & Clapper (2023)
  <https://doi.org/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.
authors:
- family-names: Lissa
  given-names: Caspar J
  name-particle: van
  email: c.j.vanlissa@tilburguniversity.edu
  orcid: https://orcid.org/0000-0002-0808-5024
- family-names: Erp
  given-names: Sara J
  name-particle: van
preferred-citation:
  type: article
  title: Selecting relevant moderators using Bayesian regularized meta-regression
  authors:
  - family-names: C. J.
    given-names: Van Lissa
  - family-names: S.
    given-names: Van Erp
  - family-names: E. B.
    given-names: Clapper
  doi: 10.31234/osf.io/6phs5
  url: https://doi.org/10.31234/osf.io/6phs5
  journal: Research Synthesis Methods
  year: '2023'
repository: https://cran.r-universe.dev
repository-code: https://github.com/cjvanlissa/pema
commit: 43c1826ff1d39c01972888d5687104bfa0595777
url: https://cjvanlissa.github.io/pema/
date-released: '2025-10-06'
contact:
- family-names: Lissa
  given-names: Caspar J
  name-particle: van
  email: c.j.vanlissa@tilburguniversity.edu
  orcid: https://orcid.org/0000-0002-0808-5024