A general model for two-level multivariate data, with responses possibly missing at random, is described. The model combines regressions on fixed explanatory variables with structured residual covariance matrices. The likelihood function is reduced to a form enabling computational methods for estimating the model to be devised. (Author)

Complex decision-making environments often demand that a range of alternative strategies be identified and compared for their shared value in achieving desired ends. Simple parametric statistical procedures such as analysis of variance and discriminant function analysis can be used in such situations to compare (using selected criteria) the value…