Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14735
Title: The analysis of multivariate longitudinal data: a review
Authors: VERBEKE, Geert 
FIEUWS, Steffen 
MOLENBERGHS, Geert 
Davidian, Marie
Issue Date: 2014
Source: Statistical methods in medical research, 23 (1), p. 42-59.
Abstract: Longitudinal experiments often involve multiple outcomes measured repeatedly within a set of study participants. While many questions can be answered by modeling the various outcomes separately, some questions canonly be answered in a joint analysis of all of them. In this article, we will present a review of the many approaches proposed in the statistical literature. Four main model families will be presented, discussed and compared. Focus will be on presenting advantages and disadvantages of the different models rather than on the mathematical or computational details.
Notes: Reprint Address: Verbeke, G (reprint author) - Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat, B-3000 Louvain, Belgium. E-mail Addresses:geert.verbeke@med.kuleuven.be
Keywords: mixed models; random effects; shared parameters; marginal models; conditional models; latent variables
Document URI: http://hdl.handle.net/1942/14735
ISSN: 0962-2802
e-ISSN: 1477-0334
DOI: 10.1177/0962280212445834
ISI #: 000330776100003
Category: A1
Type: Journal Contribution
Validations: ecoom 2015
Appears in Collections:Research publications

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