The overparameterized analysis of variance model

Analyses of variance (ANOVA) with the general linear model (GLM) in many st andard statistical packages use an overparameterized model, a model unfamil iar to most behavioral science researchers. Estimates and significance test s with GLM procedures are calculated by computing generalized inverses and estimates of estimable functions. Using simple examples, the authors discus s the concepts that underlie the solutions for 1-way and 2-way ANOVAs with overparameterized models and illustrate how these models allow one to evalu ate the research hypotheses. The authors also extend the discussion of over parameterized models to a more general modeling approach than GLM, the gene ral linear mixed model.