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weightedRank  

Sensitivity Analysis Using Weighted Rank Statistics
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("weightedRank", "0.3.7")



Attach the package and use:
library("weightedRank")
Maintained by
Paul Rosenbaum
[Scholar Profile | Author Map]
First Published: 2022-07-14
Latest Update: 2023-05-08
Description:
Performs a sensitivity analysis using weighted rank tests in observational studies with I blocks of size J; see Rosenbaum (2018) <doi:10.1214/18-AOAS1153>.The package can perform adaptive inference in block designs; see Rosenbaum (2012) <doi:10.1093/biomet/ass032>.The main functions are wgtRank() and wgtRanktt() and ef2C().
How to cite:
Paul Rosenbaum (2022). weightedRank: Sensitivity Analysis Using Weighted Rank Statistics. R package version 0.3.7, https://cran.r-project.org/web/packages/weightedRank. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.6 (2022-07-14 11:00), 0.2.5 (2023-05-08 17:50)
Other packages that cited weightedRank R package
View weightedRank citation profile
Other R packages that weightedRank depends, imports, suggests or enhances
Complete documentation for weightedRank
Functions, R codes and Examples using the weightedRank R package
Some associated functions: aBP . aHDL . amplify . dwgtRank . ef2C . weightedRank-package . wgtRank . wgtRanktt . 
Some associated R codes: amplify.R . dwgtRank.R . ef2C.R . wgtRank.R . wgtRanktt.R .  Full weightedRank package functions and examples
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