JSM 2005 - Toronto

Abstract #303092

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 192
Type: Contributed
Date/Time: Monday, August 8, 2005 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #303092
Title: Simulation Comparison of SAS Proc Multtest Permutation Adjustment Option for the Analysis of Multiple Measurements in the Two-period Crossover Design
Author(s): Mark Burgert*+
Companies: GlaxoSmithKline
Address: 104 Mill Road, Havertown, PA, 19083, United States
Keywords: multiple comparisons ; cross over design ; resampling ; simulation
Abstract:

This presentation describes the combination of two concepts---crossover designs and resampling-based multiple comparison adjustments---and shows how the combination provides an effective approach for the design and analysis of investigations with multiple responses. The basis for using the resampling options from the SAS proc multtest for the analysis of data from a two-period crossover design is presented. This description also includes the background on the use of the rank T-test as an approximation for the Wilcoxon-Mann-Whitney test. A simulation comparison of the power of Proc multtest options shows the power of permutation-adjusted T-test comparisons are equal or superior to the power of Bonferroni-adjusted comparisons. When there is an AR(1), auto-regressive correlation structure, the power of the permutation adjustment for both the T-test and the rank T-test-comparisons increases dramatically at a rho value of about 0.6. With moderate sample sizes, it is recommended that the permutation adjustment is preferred to the Bonferroni adjustment. If a nonparametric method is desired, the permutation adjustment of the rank T-test is recommended.

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