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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 |
| 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:
Downloads:
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.
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