The analysis of multivariate longitudinal data: a review

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. Geert Verbeke, Geert Molenberghs and Steffen Fieuws gratefully acknowledge support from IAP research Network P6/03 of the Belgian Government (Belgian Science Policy). The work of Marie Davidian was supported in part by NIH grants P01 CA142538, R37AI031789 and R01 CA085848.