Package: simpleFDR 1.1

Stephen Wisser

simpleFDR: Simple False Discovery Rate Calculation

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>.

Authors:Stephen C Wisser

simpleFDR_1.1.tar.gz
simpleFDR_1.1.tar.gz(r-4.7-any)simpleFDR_1.1.tar.gz(r-4.6-any)
simpleFDR_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
simpleFDR/json (API)

# Install 'simpleFDR' in R:
install.packages('simpleFDR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 168 downloads 1 exports 20 dependencies

Last updated from:be545912fa. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK97
source / vignettesOK157
linux-release-x86_64OK106
wasm-releaseOK96

Exports:simFDR

Dependencies:clicpp11dplyrgenericsgluelifecyclemagrittrpillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithr