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simpleFDR
View on CRAN: Click
here
Download and install simpleFDR package within the R console
Install from CRAN:
install.packages("simpleFDR")
Install from Github:
library("remotes")
install_github("cran/simpleFDR")
Install by package version:
library("remotes")
install_version("simpleFDR", "1.1")
Attach the package and use:
library("simpleFDR")
Maintained by
Stephen Wisser
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.simpleFDR . simpleFDR results . simpleFDR.pdf . simpleFDR_1.1.tar.gz . simpleFDR_1.1.zip . simpleFDR_1.1.zip . simpleFDR_1.1.zip . simpleFDR_1.1.tgz . simpleFDR_1.1.tgz . simpleFDR_1.1.tgz . simpleFDR_1.1.tgz . simpleFDR_1.1.tgz . simpleFDR_1.1.tgz . https://CRAN.R-project.org/package=simpleFDR .
First Published: 2021-11-04
Latest Update: 2021-11-04
Description:
Using the adjustment method from Benjamini & Hochberg (1995) <doi:10.1111/j.2517-6161.1995.tb02031.x>, this package determines which variables are significant under repeated testing with a given dataframe of p values and an user defined "q" threshold.It then returns the original dataframe along with a significance column where an asterisk denotes a significant p value after FDR calculation, and NA denotes all other p values. This package uses the Benjamini & Hochberg method specifically as described in Lee, S., & Lee, D. K. (2018) <doi:10.4097/kja.d.18.00242>.
How to cite:
Stephen Wisser (2021). simpleFDR: Simple False Discovery Rate Calculation. R package version 1.1, https://cran.r-project.org/web/packages/simpleFDR. Accessed 29 Mar. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for simpleFDR
Functions, R codes and Examples using
the simpleFDR R package
Some associated functions: simFDR .
Some associated R codes: globals.R . simFDR.R . Full simpleFDR package functions and examples
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