p.adjust {elitism}

Adjust P-values for Multiple Test Procedures

Description

Given a set of p-values, returns adjusted p-values, including the hybrid Hochberg-Hommel procedure (Gou et al., 2014) and Quick procedure (Gou and Zhang, 2022).

Usage

p.adjust(p, method = "gtxr", n = length(p))

Arguments

p

vector of p-values.

method

multiplicity correction method, "gtxr" is the hybrid Hochberg-Hommel method, "quick" is the Quick method. Other methods include:"holm", "hochberg", "hommel", "bonferroni", "BH", "BY","fdr", "none" from the standard R function p.adjust.

n

number of p-values.

Details

Given a set of p-values, returns p-values adjusted using one of several methods. The default method is "gtxr". Another option is "quick". Other adjustment methods have been included in function p.adjust in R package stats.

Value

a vector of corrected p-values.

Author(s)

Jiangtao Gou

References

Gou, J., Tamhane, A. C., Xi, D., and Rom, D. (2014). A class of improved hybrid Hochberg-Hommel type step-up multiple test procedures. Biometrika 101, 899-911.

Tamhane, A. C., and Gou, J. (2018). Advances in p-value based multiple test procedures. Journal of Biopharmaceutical Statistics 28, 10-27.

Tamhane, A. C., and Gou, J. (2022). Chapter 2 Multiple test procedures based on p-values. In X. Cui, T. Dickhaus, Y. Ding, and J. C. Hsu (Eds.), Handbook of multiple comparisons (Vol. 45, pp. 11-34).

Gou, J.(2022). Quick multiple test procedures and p-value adjustments, Statistics in Biopharmaceutical Research 14, 636-650.

See Also

stats::p.adjust

Examples

library(elitism)
 pvalues.raw <- c(0.002,0.007,0.005,0.024,0.022,0.009,0.007,0.036,0.060,0.035)
 p.adj.hoch <- elitism::p.adjust(pvalues.raw, method = "hochberg")
 p.adj.quick <- elitism::p.adjust(pvalues.raw, method = "quick")
 p.adj.gtxr <- elitism::p.adjust(pvalues.raw, method = "gtxr")