Two at a Time? Or All at Once? [Software]

posted by Helmut Homepage – Vienna, Austria, 2013-08-10 13:52 (2875 d 10:49 ago) – Posting: # 11260
Views: 14,807

Hi John,

» We actually spoke with FDA about the pool variance effect (at a conference) and they didn't seem to care. […]

I found the abstract of a 15 minutes presentation from the 2004 ENAR Spring Meeting of the IBS. Since it is so short below in all its splendor:

Donald J. Schuirmann, U.S. Food and Drug Administration

Suppose we have a bioequivalence study with three treatments – A, B, and C – and the objective of the study is to make pairwise comparisons among the treat­ments. Suppose further that treatment C is different in kind from A and B, so that the assumption of homogeneous variance among the three treatments is ques­tionable. One way to do the analyses, under normality assumptions, is Two at a Time – e.g., to test hypotheses about A and B, use only the data from A and B. Another way is All at Once – include the data from all three treatments in a single analysis, making pairwise comparisons within this analysis. If the assump­tion of homogeneous variance is correct, the All at Once approach will provide more d.f. for estimating the common variance, resulting in increased power. If the variance of C differs from that of A and B, the All at Once approach may have reduced power or an inflated type I error rate, depending on the direction of the difference in variances. I will attempt to quantify the difference between the two approaches for both the comparison of A to B and the compa­rison of A or B to C. Both parallel and crossover designs will be considered.

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