The analysis of multivariate longitudinal data: A review. (February 2014)

• Record Type: Journal Article
• Authors: Verbeke, Geert; Fieuws, Steffen; Molenberghs, Geert; Davidian, Marie
• Other Names: Rizopoulos Dimitris guest-editor.; Lesaffre Emmanuel guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 23:Number 1(2014:Feb.)
• Page Start: 42
• Page End: 59
• Publication Date: 2014-02
• Subjects: Mixed models -- random effects -- shared parameters -- marginal models -- conditional models -- latent variables; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280212445834
• Languages: English
• ISSNs: 0962-2802

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.