Package: robustmeta 1.2-1

robustmeta: Robust Inference for Meta-Analysis with Influential Outlying Studies

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>.

Authors:Hisashi Noma [aut, cre], Shonosuke Sugasawa [aut], Toshi A. Furukawa [aut]

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NEWS

# Install 'robustmeta' in R:
install.packages('robustmeta', repos = c('https://nomahi.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • clbp - Rubinstein et al. (2019)'s chronic low back pain data
  • varenicline - Thomas et al. (2015)'s varenicline data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 118 downloads 1 exports 8 dependencies

Last updated 1 years agofrom:7993550ac4. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winOKNov 02 2024
R-4.5-linuxOKNov 02 2024
R-4.4-winOKNov 02 2024
R-4.4-macOKNov 02 2024
R-4.3-winOKNov 02 2024
R-4.3-macOKNov 02 2024

Exports:rmeta

Dependencies:latticemathjaxrMatrixmetadatmetafornlmenumDerivpbapply