Abstract #301317

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JSM 2003 Abstract #301317
Activity Number: 349
Type: Invited
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract - #301317
Title: Multiple Testing in Drug Development
Author(s): Hsien-Ming James Hung*+ and Sue-Jane Wang and Robert T. O'Neill
Companies: Food and Drug Administration and Food and Drug Administration and Food and Drug Administration
Address: 9104 Orchard Brook Dr., Potomac, MD, 20854-2401,
Keywords: repeated significance test ; multiple arms ; multiple endpoints ; familywise Type I error
Abstract:

The issues with multiple analyses are unique in the areas of pharmaceutical product development. They range from repeated testing of a single statistical hypothesis to testing multiple hypotheses. The problems with the repeated significance test of the single hypothesis have mostly been resolved. For testing multiple hypotheses, no matter how best one can deal with the problem, the pre-specified decision rules often fall short to resolve controversies in practical applications. Moreover, by and large, the statistical inferences on multiple hypotheses in different contexts (e.g., multiple treatment arms, multiple endpoints) are made under the same framework, e.g., strong control of the familywise type I error rate. Another controversial problem arises in the context of requiring multiple hypotheses all to be statistically significant, such as, requiring each of the endpoints to be statistically significant. This talk is to stimulate discussion on the ways of handling these problems in different contexts. Some inference strategies and the associated designs are proposed.

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