Outlier Detection and Influence Diagnostics for Meta-Analysis
Overview
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, Noma and Gosho (2021) doi:10.1080/24709360.2021.1921944, Nakamura and Noma (2021) doi:10.5691/jjb.41.117).
- Output styles are arranged.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 7includes a package overview page
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 57%
Downloads
Dependencies
Installing boutliers adds 6 packages (1 with compiled code, 9.2 MB of source tarballs). Heaviest: metafor 4.8 MB, mathjaxr 3.0 MB, metadat 1.1 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 2.1-3Latest
- 2.1-22025-11-26 · diff ↗
- 2.1-1
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.1-2
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.1-12020-11-04
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2020-11-04
- Total releases
- 5 / 6 yrs
- License
- GPL-3 OSI
- Bundled data
- 1.8 KB / 3 files
- Download size
- 9.5 KB
Cite
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Run in R for the authors' preferred citation:
citation("boutliers")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
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