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Activity Number: 405 - Nonparametric Testing in Complex Data Settings
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #323982 View Presentation
Title: Stepwise Procedures Based on Rank Statistics in Detecting Differentially Expressed Gene
Author(s): Hossein Mansouri and Bo Li*
Companies: Texas Tech University and Montana Tech of the University of Montana
Keywords: Rank statistic ; Step-down procedure ; Multiple comparisons ; Step-up procedure ; Bootstrap ; Rank estimation
Abstract:

In this article we propose some step-down and step-up procedures based on rank statistics for analysis of data from cDNA microarrays. In classical multiple comparison methodology, stepwise procedures are known to be more powerful than the single-step procedures. We propose two classes of stepwise procedures, one based on rank statistics and a second procedure based on rank estimates for identifying differentially expressed genes. Since the distribution of the rank statistics for microarray data are often unknown, we develop a bootstrap method of conducting the tests in practice. Monte Carlo simulation is used to compare the performances of the proposed simultaneous tests to each other and to the parametric stepwise procedures and to their respective one-step competitors.


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