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has been cited by the following article:

• TITLE: A New Maximum Test via the Dependent Samples t-Test and the Wilcoxon Signed-Ranks Test

  AUTHORS: Saverpierre Maggio, Shlomo S. Sawilowsky

  KEYWORDS: Maximum Test; Dependent Samples t-Test; Wilcoxon Signed-Ranks Test; Bonferroni-Dunn Adjustment; Experiment-Wise Type I Error; Inferential Statistics; Monte Carlo Method

  JOURNAL NAME: Applied Mathematics, Vol.5 No.1, January 10, 2014

  ABSTRACT: A maximum test in lieu of forcing a choice between the two dependent samples t-test and Wilcoxon signed-ranks test is proposed. The maximum test, which requires a new table of critical values, maintains nominal α while guaranteeing the maximum power of the two constituent tests. Critical values, obtained via Monte Carlo methods, are uniformly smaller than the Bonferroni-Dunn adjustment, giving it power superiority when testing for treatment alternatives of shift in location parameter when data are sampled from non-normal distributions.