The R Journal: article published in 2014, volume 6:2

sgof: An R Package for Multiple Testing Problems
Irene Castro-Conde and Jacobo de Uña-Álvarez , The R Journal (2014) 6:2, pages 96-113.

Abstract In this paper we present a new R package called sgof for multiple hypothesis testing. The principal aim of this package is to implement SGoF-type multiple testing methods, known to be more powerful than the classical false discovery rate (FDR) and family-wise error rate (FWER) based methods in certain situations, particularly when the number of tests is large. This package includes Bi nomial and Conservative SGoF and the Bayesian and Beta-Binomial SGoF multiple testing procedures, which are adaptations of the original SGoF method to the Bayesian setting and to possibly correlated tests, respectively. The sgof package also implements the Benjamini-Hochberg and Benjamini-Yekutieli FDR controlling procedures. For each method the package provides (among other things) the number of rejected null hypotheses, estimation of the corresponding FDR, and the set of adjusted p values. Some automatic plots of interest are implemented too. Two real data examples are used to illustrate how sgof works.

Received: 2014-04-18; online 2014-11-24
CRAN packages: sgof, mutoss, multcomp
CRAN Task Views implied by cited CRAN packages: ClinicalTrials, SocialSciences, Survival
Bioconductor packages: qvalue, HybridMTest, multtest

This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2014-027,
  author = {Irene Castro-Conde and Jacobo de Uña-Álvarez},
  title = {{sgof: An R Package for Multiple Testing Problems}},
  year = {2014},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2014-027},
  url = {https://doi.org/10.32614/RJ-2014-027},
  pages = {96--113},
  volume = {6},
  number = {2}
}