  Most of the available multivariate statistical models dictate on fitting
different parameters for the covariate effects on each multiple responses. This
might be unnecessary and inefficient for some cases. In this article, we
propose a modeling framework for multivariate marginal models to analyze
multivariate longitudinal data which provides flexible model building
strategies. We show that the model handles several response families such as
binomial, count and continuous. We illustrate the model on the Mother's Stress
and Children's Morbidity data set. A simulation study is conducted to examine
the parameter estimates. An R package mmm2 is proposed to fit the model.
