Abstract #301723

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JSM 2003 Abstract #301723
Activity Number: 97
Type: Contributed
Date/Time: Monday, August 4, 2003 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract - #301723
Title: Modeling Dropouts in Analyzing Data from Psychiatry Clinical Trials
Author(s): Yonghua Wang*+
Companies: GlaxoSmithKline
Address: 5 Moore Dr., Research Triangle Park, NC, 27709,
Keywords: dropouts ; proper analysis ; distribution ; modeling
Abstract:

One of the major issues in psychiatry clinical trials is high dropout rate. There are many methods to handle the missing data for dropout subjects. These methods include last observation carried forward, repeated measure method, and mixed model method. When these methods are used, the nature of dropout itself is usually ignored. This may result in underfit for all models used. The results from these models may not be valid. Properly analyzing data from psychiatry clinical trials is discussed around the dropouts. Modeling dropouts to improve the accuracy of treatment comparison and to increase the validity and/or properness of statistical analysis is proposed.

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