Analysis of Covariance in GRM

Select Analysis of covariance on the General Regression Models Startup Panel - Quick tab to specify analysis of covariance (ANCOVA and MANCOVA) designs. In the subsequent Quick specs dialog box, specify one or more categorical predictor variables, one or more continuous predictor variables, and one or more dependent variables (MANCOVA). By default, Statistica will estimate and evaluate the full factorial model for the categorical predictors, and the main-effects model for the continuous predictors.

Analysis of covariance models are often used to "control" for the effects of extraneous (to the experiment) variables on the dependent variable. For example, an educational researcher may use student's IQ (measured intelligence) as a covariate in a research design evaluating the efficacy of various teaching methods. For more information, refer to the Introductory Overview. See also GRM - Index.