kfwe-package: Controlling the k-FWER (Generalized Familywise Error Rate)

In someKfwer: Controlling the Generalized Familywise Error Rate

Description

This package collects some procedures controlling the Generalized Familywise Error Rate: Lehmann and Romano (2005), Guo and Romano (2007) (single step and stepdown), Finos and Farcomeni (2009).

Details

Package:	kfwe
Type:	Package
Version:	1.0
Date:	2009-10-30
License:	GPL (>= 2)
LazyLoad:	yes

Author(s)

L. Finos and A. Farcomeni

Maintainer: <[e-mail]>

References

Finos and Farcomeni (2010) k-FWER control without multiplicity correction, with application to detection of genetic determinants of multiple sclerosis in Italian twins. Biometrics (Articles online in advance of print: DOI 10.1111/j.1541-0420.2010.01443.x)

Examples

set.seed(13)
y=matrix(rnorm(3000),3,1000)+2                      #create toy data
p=apply(y,2,function(y) t.test(y)$p.value)          #compute p-values
M2=apply(y^2,2,mean)                                #compute ordering criterion

kord=kfweOrd(p,k=5,ord=M2)                          #ordinal procedure
kgr=kfweGR(p,k=5)                                   #Guo and Romano

kord=kfweOrd(p,k=5,ord=M2,GD=TRUE)                  #ordinal procedure (any dependence)
klr=kfweLR(p,k=5)                                   #Lehaman and Romano (any dependence)

Example output

Ordered k-FWER procedure
 1000 tests, k=5, alpha=0.01, individual alpha threshold=0.01
 125 jumps allowed
 32 rejections

Guo and Romano k-FWER Step Down procedure
 1000 tests, k=5, alpha=0.01
 0.0013057 individual alpha threshold
 23 rejections

Ordered k-FWER procedure
 1000 tests, k=5, alpha=0.01, individual alpha threshold=0.0003846
 125 jumps allowed
 0 rejections

Lehmann e Romano k-FWER Step Down procedure
 1000 tests, k=5, alpha=0.01
 1 rejections

someKfwer documentation built on May 1, 2019, 10:19 p.m.