Abstract #301545

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JSM 2003 Abstract #301545
Activity Number: 180
Type: Contributed
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #301545
Title: A Comparison Between Andersen-Gill and Lin-Wei-Yang-Ying Model for Hypoglycemia Data
Author(s): Boll Wu*+ and Robert Costello and Lu Tian
Companies: Aventis Pharmaceuticals, Inc. and Aventis Pharmaceuticals, Inc. and Harvard School of Public Health
Address: 200 Crossing Blvd., Bridgewater, NJ, 08807-2861,
Keywords: counting process ; intensity function ; clinical trials ; mean regression ; hypoglycemia ; Poisson process
Abstract:

In diabetes disease, hypoglycemia is sometimes a recurrent event and by the nature, the current event may be related with previous one, i.e., if a patient had an event, the chance of having another event for this patient is higher than those having none before. Andersen-Gill model with the Cox-type intensity function has been the popular choice in the clinical trials for the counting process. This model essentially assumes that the intensity of the counting process is a nonhomogenous Poisson with baseline covaraites. Recently, Lin, Wei, Yang and Ying (LWYY) (2000) relaxed this assumption by modeling the marginal mean function of the counting process. The estimate studied by Andersen and Gill is still consistent for the regression coefficients under the general mean model. LWYY proposes a robust variance estimate for the regression parameter estimate. We discuss those two methods and present simulation results with mocked hypoglycemia data of a clinical trial in which the Poisson assumption is mildly violated.

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