The analysis of longitudinal ordinal data with nonrandom drop-out

Molenberghs, G. and Kenward, Michael G. and Lesaffre, E. (1997) The analysis of longitudinal ordinal data with nonrandom drop-out. Biometrika, 84 (1). pp. 33-44. ISSN 0006-3444. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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A model is proposed for longitudinal ordinal data with nonrandom drop-out, which combines the multivariate Dale model for longitudinal ordinal data with a logistic regression model for drop-out. Since response and drop-out are modelled as conditionally independent given complete data, the resulting likelihood can be maximised relatively simply, using the EM algorithm, which with acceleration is acceptably fast and, with appropriate additions, can produce estimates of precision. The approach is illustrated with an example. Such modelling of nonrandom drop-out requires caution because the interpretation of the fitted models depends on assumptions that are unexaminable in a fundamental sense, and the conclusions cannot be regarded as necessarily robust. The main role of such modelling may be as a component of a sensitivity analysis.

Item Type: Article
Uncontrolled keywords: Dale model; EM algorithm; global odds ratio; marginal model; missing values; repeated measurements
Subjects: Q Science
Q Science > QH Natural history > QH301 Biology
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science
Depositing User: M.A. Ziai
Date Deposited: 18 Apr 2009 18:13
Last Modified: 11 Jul 2014 09:18
Resource URI: (The current URI for this page, for reference purposes)
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