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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1 |
rolling linux/jammy R-4.5 | simpleFDR_1.1.tar.gz |
10.2 KiB |
1.1 |
rolling linux/noble R-4.5 | simpleFDR_1.1.tar.gz |
10.1 KiB |
1.1 |
rolling source/ R- | simpleFDR_1.1.tar.gz |
2.2 KiB |
1.1 |
latest linux/jammy R-4.5 | simpleFDR_1.1.tar.gz |
10.2 KiB |
1.1 |
latest linux/noble R-4.5 | simpleFDR_1.1.tar.gz |
10.1 KiB |
1.1 |
latest source/ R- | simpleFDR_1.1.tar.gz |
2.2 KiB |
1.1 |
2026-04-26 source/ R- | simpleFDR_1.1.tar.gz |
2.2 KiB |
1.1 |
2026-04-23 source/ R- | simpleFDR_1.1.tar.gz |
2.2 KiB |
1.1 |
2026-04-09 windows/windows R-4.5 | simpleFDR_1.1.zip |
13.2 KiB |
1.1 |
2025-04-20 source/ R- | simpleFDR_1.1.tar.gz |
2.2 KiB |