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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/330

Title: The Analysis of Longitudinal Ordinal Data with Non-random Dropout
Authors: Molenberghs, Geert
Kenward, Michael
Lesaffre, Emmanuel
Keywords: Longitudinal data
Missing data
Issue Date: 1997
Citation: BIOMETRIKA, 84(1), p. 33-44
Abstract: 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 dropout. 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
URI: http://hdl.handle.net/1942/330
Link to publication: https://www.academia.edu/8393354/The_analysis_of_longitudinal_ordinal_data_with_nonrandom_drop-out
DOI: 10.1093/biomet/84.1.33
ISI #: A1997WT08200003
ISSN: 0006-3444
Type: Journal Contribution
Appears in Collections: Research publications

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