Analysis of Covariance in GLM, GLZ, and PLS

Select Analysis of covariance as the Type of analysis on the GLM Startup Panel - Quick tab to specify Analysis of Covariance (ANCOVA, MANCOVA) designs. In the subsequent Quick Specs dialog box, you can 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 students' 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, GLM - Index, and General ANOVA/MANOVA and GLM Notes - Covariates.