Sensitivity Analyses for Unmeasured Confounding and Other Biases in Observational Studies and Meta-Analyses R package EValue version 4.1.4 CRAN Task View: CausalInference (https://CRAN.R-project.org/view=CausalInference) CRAN Task View: MetaAnalysis (https://CRAN.R-project.org/view=MetaAnalysis) Conducts sensitivity analyses for unmeasured confounding, selection bias, and measurement error (individually or in combination; VanderWeele & Ding (2017) <doi:10.7326/M16-2607>; Smith & VanderWeele (2019) <doi:10.1097/EDE.0000000000001032>; VanderWeele & Li (2019) <doi:10.1093/aje/kwz133>; Smith, Mathur, & VanderWeele (2021) <doi:10.1097/EDE.0000000000001380>). Also conducts sensitivity analyses for unmeasured confounding in meta-analyses (Mathur & VanderWeele (2020a) <doi:10.1080/01621459.2018.1529598>; Mathur & VanderWeele (2020b) <doi:10.1097/EDE.0000000000001180>) and for additive measures of effect modification (Mathur et al., <doi:10.1093/ije/dyac073>). Software Imports: stats, graphics, ggplot2 (>= 2.2.1), metafor, methods, boot, MetaUtility, dplyr Suggests: testthat, knitr, rmarkdown, metadat Maya B. Mathur <mmathur@stanford.edu> Comprehensive R Archive Network (CRAN) Maya B. Mathur [cre, aut], Louisa H. Smith [aut], Peng Ding [aut], Tyler J. VanderWeele [aut] GPL-2 2025-08-28 application/tgz https://CRAN.R-project.org/package=EValue doi:10.32614/CRAN.package.EValue