Abstract #301861

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JSM 2003 Abstract #301861
Activity Number: 203
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor: ENAR
Abstract - #301861
Title: A Hybrid Model for Longitudinal Binary Responses Subject to Nonignorable Dropout
Author(s): Kenneth J. Wilkins*+ and Garrett M. Fitzmaurice
Companies: Harvard School of Public Health and Harvard School of Public Health
Address: Dept. of Biostatistics, Boston, MA, 02115-6009,
Keywords: Binary outcome ; dropout ; longitudinal ; missing data ; nonignorable
Abstract:

This paper presents a likelihood-based method for handling nonignorable dropout in longitudinal studies with binary responses. The methodology developed here is appropriate when the target of inference is the marginal distribution of the response at each occasion and its dependence on covariates. A "hybrid" model is formulated which is designed to retain the most advantageous features of the selection and pattern-mixture model approaches. This formulation accommodates a variety of assumed forms of nonIgnorable dropout, while maintaining transparency of the constraints required for identifying the overall model. Once appropriate identifying constraints have been imposed, likelihood-based estimation is conducted via the EM algorithm. The paper concludes by applying the approach to an example using data from a randomized clinical trial.

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