EValue: Sensitivity Analyses for Unmeasured Confounding and Other Biases in Observational Studies and Meta-Analyses

Conducts sensitivity analyses for unmeasured confounding,selection bias, and measurement error (individually or in combination) in individual studies. Also conducts sensitivity analyses for unmeasured confounding in meta-analyses.

Version: 4.1.0
Imports: stats, graphics, ggplot2 (≥ 2.2.1), metafor, methods, boot, MetaUtility, dplyr
Suggests: testthat, knitr, rmarkdown
Published: 2020-11-18
Author: Maya B. Mathur [cre, aut], Louisa H. Smith [aut], Peng Ding [aut], Tyler J. VanderWeele [aut]
Maintainer: Maya B. Mathur <mmathur at stanford.edu>
License: GPL-2
NeedsCompilation: no
Citation: EValue citation info
Materials: README
In views: MetaAnalysis
CRAN checks: EValue results

Downloads:

Reference manual: EValue.pdf
Vignettes: Unmeasured confounding in meta-analyses
Examples of multiple-bias sensitivity analysis
E-values for multiple biases
E-values for selection bias
E-value equivalents for meta-analysis
Package source: EValue_4.1.0.tar.gz
Windows binaries: r-devel: EValue_4.1.0.zip, r-release: EValue_4.1.0.zip, r-oldrel: EValue_4.1.0.zip
macOS binaries: r-release: EValue_4.1.0.tgz, r-oldrel: EValue_4.1.0.tgz
Old sources: EValue archive

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