Methods exist for testing the homogeneity of group regression for the case in which there is only one predictor. Studies which have investigated aptitude-treatment interactions have adopted the homogeneity of regressions test as standard methodology for assessing the difference in regression slopes across treatments. Additional statistical methodology is suggested by which the homogeneity of group regressions can be tested when two or more predictors are present. Before covariate analysis can be used, the homogeneity of group regression must be tested. To test the hypothesis that the slopes are equal for the homogeneity of group regressions for a single covariate, one can follow the standard linear prediction model. For the case in which there are multiple covariates, a test for homogeneity of regressions provides an overall estimate of the difference between treatments, taking into account the effect of the multiple covariates upon each treatment, simultaneously. Partial hypotheses for a multiple covariate model are presented in order to isolate the cause of overall interaction when treatment slopes with multiple covariates are not equal. Data from two aptitude-treatment investigations are used to illustrate the equations. (CK)