bonholm: Bonferonni-Holm Correction

In Dynge/r_dynge: Dynge's Useful Functions

Description

This function computes the bonferroni-holm correction and determines if the p-values entered are significant or not.

Usage

bonholm(p_vals, alpha = 0.05)

Arguments

p_vals	Enter a vector of p-values to compute the bonferroni-holm correction on.
alpha	The alpha level of you significance test.

Value

nSig	The number of significant results.
p_val	The significant p-values.
n	The amount of p-values corrected. The same as the length of your input vector.
data	A dataset containing the p-values, their respective adjusted alpha level, aswell as a boolean indicating if the p-value is significant or not.

Examples

p_vals <- lapply(seq_len(ncol(mtcars)), function(x) shapiro.test(mtcars[[x]]))
adjust_p <- bonholm(p_vals)
adjust_p

Dynge/r_dynge documentation built on July 1, 2019, 11:21 p.m.