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:
simpleFDR_1.1.tar.gz
simpleFDR_1.1.tar.gz(r-4.5-noble)simpleFDR_1.1.tar.gz(r-4.4-noble)
simpleFDR_1.1.tgz(r-4.4-emscripten)simpleFDR_1.1.tgz(r-4.3-emscripten)
simpleFDR.pdf |simpleFDR.html✨
simpleFDR/json (API)
| # Install 'simpleFDR' in R: |
| install.packages('simpleFDR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:be545912fa. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 02 2024 |
| R-4.5-linux | OK | Sep 02 2024 |
Exports:simFDR
Dependencies:clicpp11dplyrfansigenericsgluelifecyclemagrittrpillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Simple False Discovery Rate (FDR) Calculation | simFDR |