metaforest: Exploring Heterogeneity in Meta-Analysis using Random Forests
Conduct random forests-based meta-analysis, obtain partial dependence plots for metaforest and classic meta-analyses, and cross-validate and tune metaforest- and classic meta-analyses in conjunction with the caret package. A requirement of classic meta-analysis is that the studies being aggregated are conceptually similar, and ideally, close replications. However, in many fields, there is substantial heterogeneity between studies on the same topic. Classic meta-analysis lacks the power to assess more than a handful of univariate moderators. MetaForest, by contrast, has substantial power to explore heterogeneity in meta-analysis. It can identify important moderators from a larger set of potential candidates (Van Lissa, 2020). This is an appealing quality, because many meta-analyses have small sample sizes. Moreover, MetaForest yields a measure of variable importance which can be used to identify important moderators, and offers partial prediction plots to explore the shape of the marginal relationship between moderators and effect size.
| Version: | 0.1.5 |
| Depends: | R (≥ 3.5.0),ggplot2 |
| Imports: | gtable, grid,data.table,metafor,ranger, methods,metadat |
| Suggests: | testthat,caret,knitr,rmarkdown,covr |
| Published: | 2025-07-30 |
| DOI: | 10.32614/CRAN.package.metaforest |
| Author: | Caspar J. Van Lissa [aut, cre] |
| Maintainer: | Caspar J. Van Lissa <c.j.vanlissa at gmail.com> |
| BugReports: | https://github.com/cjvanlissa/metaforest/issues |
| License: | GPL-3 |
| URL: | https://cjvanlissa.github.io/metaforest/,https://github.com/cjvanlissa/metaforest |
| NeedsCompilation: | no |
| Citation: | metaforest citation info |
| Materials: | README,NEWS |
| In views: | MetaAnalysis |
| CRAN checks: | metaforest results |
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