WMAP: Weighted Meta-Analysis with Pseudo-Populations

Implementation of integrative weighting approaches for multiple observational studies and causal inferences. The package features three weighting approaches, each representing a special case of the unified weighting framework, introduced by Guha and Li (2024) <doi:10.1093/biomtc/ujae070>, which includes an extension of inverse probability weights for data integration settings.

Version: 1.3.0
Depends: R (≥ 3.5.0)
Imports: pkgcond, ggplot2, zeallot, randomForest, ranger, forcats, utils, stats
Suggests: future (≥ 1.33.0), future.apply (≥ 1.11.0), parallelly (≥ 1.37.0), knitr, rmarkdown
Published: 2026-06-05
DOI: 10.32614/CRAN.package.WMAP
Author: Subharup Guha [aut, cre], Mengqi Xu [aut], Chayce Reed [aut], Kashish Priyam [aut], Yi Li [aut]
Maintainer: Subharup Guha <Subharup.Guha at dartmouth.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: WMAP results

Documentation:

Reference manual: WMAP.html , WMAP.pdf
Vignettes: WMAP (source, R code)

Downloads:

Package source: WMAP_1.3.0.tar.gz
Windows binaries: r-devel: WMAP_1.2.0.zip, r-release: WMAP_1.2.0.zip, r-oldrel: WMAP_1.2.0.zip
macOS binaries: r-release (arm64): WMAP_1.3.0.tgz, r-oldrel (arm64): WMAP_1.3.0.tgz, r-release (x86_64): WMAP_1.3.0.tgz, r-oldrel (x86_64): WMAP_1.3.0.tgz
Old sources: WMAP archive

Linking:

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