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EValue  

Sensitivity Analyses for Unmeasured Confounding and Other Biases in Observational Studies and Meta-Analyses
View on CRAN: Click here


Download and install EValue package within the R console
Install from CRAN:
install.packages("EValue")

Install from Github:
library("remotes")
install_github("cran/EValue")

Install by package version:
library("remotes")
install_version("EValue", "4.1.3")



Attach the package and use:
library("EValue")
Maintained by
Maya B. Mathur
[Scholar Profile | Author Map]
First Published: 2017-10-30
Latest Update: 2021-10-28
Description:
Conducts sensitivity analyses for unmeasured confounding, selection bias, and measurement error (individually or in combination; VanderWeele & Ding (2017) ; Smith & VanderWeele (2019) ; VanderWeele & Li (2019) ; Smith & VanderWeele (2021) ). Also conducts sensitivity analyses for unmeasured confounding in meta-analyses (Mathur & VanderWeele (2020a) ; Mathur & VanderWeele (2020b) ) and for additive measures of effect modification (Mathur et al., under review).
How to cite:
Maya B. Mathur (2017). EValue: Sensitivity Analyses for Unmeasured Confounding and Other Biases in Observational Studies and Meta-Analyses. R package version 4.1.3, https://cran.r-project.org/web/packages/EValue. Accessed 06 May. 2025.
Previous versions and publish date:
1.0.0 (2017-10-30 12:21), 1.1.0 (2017-11-29 14:31), 1.1.1 (2017-12-21 22:50), 1.1.2 (2018-03-29 00:45), 1.1.3 (2018-04-04 00:52), 1.1.4 (2018-05-18 23:51), 1.1.5 (2018-09-18 17:20), 2.0.0 (2019-04-01 15:20), 2.1.0 (2020-05-17 07:00), 3.0.0 (2020-06-16 16:10), 4.1.0 (2020-11-18 21:50), 4.1.1 (2021-01-04 18:40), 4.1.2 (2021-04-01 23:40)
Other packages that cited EValue R package
View EValue citation profile
Other R packages that EValue depends, imports, suggests or enhances
Complete documentation for EValue
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