o Homogeneity of regression. The covariate coefficients (the slopes of the regression lines) are the same for each group formed by the categorical variables and measured on the dependents. The more this assumption is violated, the more conservative MANCOVA becomes (the more likely it is to make Type I errors - accepting a false null hypothesis). When running a MANCOVA model in SPSS, include in the model options the interactions between the covariate(s) and each independent variable -- any significant interaction effects indicate that the assumption of homogeneity of regression coefficients has been violated. See the discussion in the section on testing assumptions.
o Sphericity. In a repeated measures design, the univariate ANOVA tables will not be interpreted properly unless the variance/covariance matrix of the dependent variables is circular in form (see Huynh and Mandeville, 1979). When there is a violation of this assumption, a common option then is to focus on the multivariate (simultaneous) approach to gauging effects.