Grender J M, Johnson W D
Department of Biometry and Genetics, Louisiana State University Medical Center, New Orleans 70112.
Stat Med. 1993 Jan 15;12(1):69-89. doi: 10.1002/sim.4780120108.
Crossover designs involve observing the same response variate under different experimental conditions for each subject. Univariate methods are commonly used for analysis of data arising in these designs, but multivariate procedures offer a more general approach. The general multivariate linear model provides a natural framework for the simplest data structure as well as more complex settings with two or more response variates and measurements repeated over time. Multivariate models for crossover designs provide a unified approach that clarifies specification of hypotheses, assumptions required, and testing procedures in a wide class of applications that include longitudinal data as a special case. We focus on the 2 x 2 crossover design, but also describe models for analysing more complex crossover designs.
