iAWvar.TrimMean: Test for equality of variance based on improved Ahn and...

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

Description

Test for equality of variance based on improved Ahn and Wang's (2013) score test.

Usage

iAWvar.TrimMean(value, group, trim.alpha = 0.25)

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).
trim.alpha	numeric. Indicating proportion of data points to be trimmed from both ends before calculating sample mean.

Value

A list with 6 elements:

U2	score statistic
varU2	estimated variance of the score statistic
T2	score statistic U2^2/varU2
pval	pvalue of the score test
z	absolute deviation of value from trimmed-mean of value
zbar	sample average of z

Author(s)

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

References

Li X, Qiu W, Morrow J, DeMeo DL, Weiss ST, Fu Y, Wang X. (2015) A Comparative Study of Tests for Homogeneity of Variances with Application to DNA Methylation Data. PLoS ONE 10(12): e0145295. PMID: 26683022

Qiu W, Li X, Morrow J, DeMeo DL, Weiss ST, Wang X, Fu Y. New Score Tests for Equality of Variances in the Application of DNA Methylation Data Analysis [Version 2]. Insights Genet Genomics. (2017) 1: 3.2

Li X, Qiu W, Fu Y, Wang X. (2017) Robust Joint Score Tests in the Application of DNA Methylation Data Analysis. In submission.

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

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