title: The analysis of multivariate longitudinal data: a review.
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 can only 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.
authors.affiliation: 1Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, B-3000 Leuven, Belgium.
authors.forename: Geert
authors.initials: G
authors.lastname: Verbeke
authors.forename: Steffen
authors.initials: S
authors.lastname: Fieuws
authors.forename: Geert
authors.initials: G
authors.lastname: Molenberghs
authors.forename: Marie
authors.initials: M
authors.lastname: Davidian
mesh_terms: D006309:Hearing; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D015999:Multivariate Analysis