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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/396

Title: A review on linear mixed models for longitudinal data, possibly subject to dropout
Authors: Molenberghs, Geert
Verbeke, Geert
Keywords: Longitudinal data
Missing data
Issue Date: 2001
Citation: STATISTICAL MODELLING, 1(4). p. 235-269
Abstract: Many approaches are available for the analysis of continuous longitudinal data. Over the last couple of decades, a lot of emphasis has been put on the linear mixed model. The current paper is dedicated to an overview of this approach, with emphasis on model formulation, interpretation and inference. Advantages as well as drawbacks are discussed, and guidelines are given for general statistical practice. Special attention is given to the problem of missing data, i.e., the case where not all data are present as planned in the original design of the study.
URI: http://hdl.handle.net/1942/396
Link to publication: https://www.researchgate.net/publication/243102774_A_review_on_linear_mixed_models_for_longitudinal_data_possibly_subject_to_dropout
DOI: 10.1177/1471082X0100100402
ISSN: 1471-082X
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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