Simple False Discovery Rate Calculation

Using the adjustment method from Benjamini & Hochberg (1995) , 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) .


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install.packages("simpleFDR")

1.1 by Stephen Wisser, a month ago


Browse source code at https://github.com/cran/simpleFDR


Authors: Stephen C Wisser


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports dplyr, tidyr


See at CRAN