robustmeta
1.2-1Robust Inference for Meta-Analysis with Influential Outlying Studies
Overview
Robust inference methods for fixed-effect and random-effects models of meta-analysis are implementable. The robust methods are developed using the density power divergence that is a robust estimating criterion developed in machine learning theory, and can effectively circumvent biases and misleading results caused by influential outliers. The density power divergence is originally introduced by Basu et al. (1998) doi:10.1093/biomet/85.3.549, and the meta-analysis methods are developed by Noma et al. (2022) <forthcoming>.
Install
Health
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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Dependencies
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Code & Tests
- Cyclomatic complexity
- 2.0 median / 8 max
- Documented parameters
- 100%
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
6 1 exported
Complexity
3.8 avg / 8 max
Call network
6 nodes / 4 edges
Test coverage has not been measured for this package yet; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.2-1Latest
- RR 4.3.0 released · 2023-04-21
- 1.1-12022-07-21
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-07-21
- Total releases
- 2 / 4 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 1.2 KB / 2 files
- Download size
- 6.2 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet