  For gene expression data measured in a crossover trial, a multivariate
mixed-effects model seems to be most appropriate. Standard statistical
inference fails to provide reliable results when some responses are missing.
Particularly for crossover studies, missingness is a serious concern as the
trial requires a small number of participants. A Monte Carlo EM (MCEM) based
technique has been adopted to deal with this situation. Along with estimation,
a MCEM likelihood ratio test (LRTs) is developed for testing the fixed effects
in such a multivariate crossover model with missing data. Intensive simulation
studies have been carried out prior to the analysis of the gene expression
data.
