boutliers: Outlier Detection and Influence Diagnostics for Meta-Analysis

Computational tools for outlier detection and influence diagnostics in meta-analysis (Noma et al. (2025) <doi:10.1101/2025.09.18.25336125>). Bootstrap distributions of influence statistics are computed, and explicit thresholds for identifying outliers are provided. These methods can also be applied to the analysis of influential centers or regions in multicenter or multiregional clinical trials (Aoki and Noma (2021) <doi:10.1080/24709360.2021.1921944>, Nakamura and Noma (2021) <doi:10.5691/jjb.41.117>).

Version:	2.1-1
Imports:	stats, metafor, MASS
Published:	2025-09-20
Author:	Hisashi Noma [aut, cre], Kazushi Maruo [aut], Masahiko Gosho [aut]
Maintainer:	Hisashi Noma <noma at ism.ac.jp>
License:	GPL-3
NeedsCompilation:	no
Materials:	README, NEWS
In views:	MetaAnalysis
CRAN checks:	boutliers results

Documentation:

Reference manual:

boutliers.html , boutliers.pdf

Downloads:

Package source:	boutliers_2.1-1.tar.gz
Windows binaries:	r-devel: boutliers_2.1-1.zip, r-release: boutliers_2.1-1.zip, r-oldrel: boutliers_2.1-1.zip
macOS binaries:	r-release (arm64): boutliers_2.1-1.tgz, r-oldrel (arm64): boutliers_2.1-1.tgz, r-release (x86_64): boutliers_2.1-1.tgz, r-oldrel (x86_64): boutliers_2.1-1.tgz
Old sources:	boutliers archive

Linking:

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