Comparative review of methods for handling drop-out in longitudinal studies

Philipson, Pete, Ho, Weang Kee and Henderson, Robin (2008) Comparative review of methods for handling drop-out in longitudinal studies. Statistics in Medicine, 27 (30). pp. 6276-6298. ISSN 0277-6715

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Longitudinal data analysis is frequently complicated by drop-out. In this paper we consider several methods for dealing with drop-out afflicted data. Along with a general comparison, particular attention is paid to the consequences of model misspecification. The purpose of our approach is two-fold. We first deliberate the form of the drop-out model and compare two alternatives. Furthermore, the extent to which each method is dependent on its core assumptions is assessed through scenarios where one or more such assumptions are compromised. Second, the extent to which we can identify adequacy of model fit is investigated via recently developed diagnostics. These twin targets are pursued via simulation scenarios and application to a schizophrenia trial of over 500 patients with near 50 per cent drop-out.

Item Type: Article
Uncontrolled Keywords: missing data, diagnostics, sensitivity analysis, inverse probability weighting, random effects
Subjects: G100 Mathematics
G300 Statistics
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Ay Okpokam
Date Deposited: 08 Feb 2012 15:45
Last Modified: 13 Oct 2019 00:25

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