Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sa

Background: In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio) is biologically meaningless. A relevant difference or ratio is sought in such cases. Results: This article addresses the use of relevance-shifted tests on ratios for a multivariate parallel two-sample group design. Two empirical procedures are proposed which embed the relevanceshifted test on ratios. As both procedures test a hypothesis for each variable, the resulting multiple testing problem has to be considered. Hence, the procedures include a multiplicity correction. Both procedures are extensions of available procedures for point null hypotheses achieving exact control of the familywise error...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Cornelia Frömke, Ludwig A. Hothorn, Siegfried Kropf
• Keywords: BMCBI 2008, Microarray Data, Null Hypothesis, Procedure