BFtest: Test for equality of variance based on Brown and Forsythe's...

In diffMeanVar: Detecting Gene Probes with Different Means or Variances Between Two Groups

Description

Test for equality of variance based on Brown and Forsythe's test.

Usage

BFtest(value, group)

Arguments

value	numeric. Measurements to be compared between two groups.
group	numeric. Subject's group membership. Must be binary (i.e., taking values 0 or 1).

Value

A list with 2 elements:

stat	test statistic value
pval	pvalue of the score test

Author(s)

Xuan Li <[e-mail]>, Weiliang Qiu <[e-mail]>, Yuejiao Fu <[e-mail]>, Xiaogang Wang <[e-mail]>

References

Brown MB and Forsythe AB (1974) Robust Tests for Equality of Variances. Journal of the American Statistical Association, 69, 364-367.

Examples

    # generate simulated data set from t distribution
    set.seed(1234567)
    es.sim = genSimData.tDistr(nCpGs = 100, nCases = 20, nControls = 20,
      df0 = 10, ncp0 = 0, df1 = 6, ncp1 = 2.393, testPara = "var",
      eps = 1.0e-3, applier = lapply) 
    print(es.sim)
    print(exprs(es.sim)[1:2,1:3])

    # do AW score test for the first probe
    dat = exprs(es.sim)
    pDat = pData(es.sim)
    print(pDat[1:2,])

    res = BFtest(value = dat[1,], group = pDat$memSubj)
    print(names(res))
    print(res)

diffMeanVar documentation built on May 2, 2019, 2:54 a.m.