1983 Volume 10 Issue 13 Pages 47-57
This paper presents a simplified approach to Bayesian multivariate analysis of variance (MANOVA) using a cell mean parametrization with specific application to growth curve analysis. With the proposed approach for MANOVA, all cell mean vectors and multivariate treatment contrasts are estimable regardless of the nature of the design when appropriate prior distributions are specified. With the usual multivariate normal model, the distributions of linear contrasts of vector cell means are shown to be obtainable from a matric-variate t distribution. Polynomial effects of time are also considered in order to provide a model for the analysis of longitudinal data.
