multibiasmeta: Sensitivity Analysis for Multiple Biases in Meta-Analyses

Meta-analyses can be compromised by studies' internal biases (e.g., confounding in nonrandomized studies) as well as by publication bias. This package conducts sensitivity analyses for the joint effects of these biases (per Mathur (2022) <doi:10.31219/>). These sensitivity analyses address two questions: (1) For a given severity of internal bias across studies and of publication bias, how much could the results change?; and (2) For a given severity of publication bias, how severe would internal bias have to be, hypothetically, to attenuate the results to the null or by a given amount?

Version: 0.2.2
Depends: R (≥ 4.1.0)
Imports: dplyr, EValue, metabias, metafor, purrr, Rdpack, rlang, robumeta
Suggests: glue, knitr, phacking, PublicationBias (≥ 2.3.0), rmarkdown, testthat (≥ 3.0.0)
Published: 2023-08-23
DOI: 10.32614/CRAN.package.multibiasmeta
Author: Maya Mathur [aut], Mika Braginsky [aut], Peter Solymos ORCID iD [cre, ctb]
Maintainer: Peter Solymos <peter at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
In views: MetaAnalysis
CRAN checks: multibiasmeta results


Reference manual: multibiasmeta.pdf
Vignettes: tutorial


Package source: multibiasmeta_0.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): multibiasmeta_0.2.2.tgz, r-oldrel (arm64): multibiasmeta_0.2.2.tgz, r-release (x86_64): multibiasmeta_0.2.2.tgz, r-oldrel (x86_64): multibiasmeta_0.2.2.tgz
Old sources: multibiasmeta archive


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