Molenberghs, G. and Kenward, M.G. and Lesaffre, E. (1997) The analysis of longitudinal ordinal data with nonrandom drop-out. Biometrika, 84 (1). pp. 33-44. ISSN 0006-3444.
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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.
|Uncontrolled keywords:||Dale model; EM algorithm; global odds ratio; marginal model; missing values; repeated measurements|
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:||18 Apr 2009 18:13|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/18195 (The current URI for this page, for reference purposes)|
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