GLM Hypothesis Testing - Designs with Zero Degrees of Freedom for Error

When the model degrees of freedom equal the number of cases or subjects, the residual sums of squares will have zero degrees of freedom and preclude the use of standard hypothesis tests. This sometimes occurs for overfitted designs (designs with many predictors, or designs with categorical predictors having many levels). However, in some designed experiments, such as experiments using split-plot designs or highly fractionalized factorial designs as commonly used in industrial experimentation, it is no accident that the residual sum of squares has zero degrees of freedom. In such experiments, mean squares for certain effects are planned to be used as error terms for testing other effects, and the experiment is designed with this in mind. It is entirely appropriate to use alternatives to the mean square residual as error terms for testing hypotheses in such designs (see also the Examples section of the Experimental Design module).

Whole Model Tests

Six Types of Sums of Squares

Error Terms for Tests

Testing Specific Hypotheses

Testing Hypotheses for Repeated Measures and Dependent Variables