MANOVA and General Linear Model (GLM) (MANOVA command)

MANOVA is available only in syntax. GLM (general linear model), the other generalized procedure for analysis of variance and covariance, is available both in syntax and via the dialog boxes. The major distinction between GLM and MANOVA in terms of statistical design and functionality is that GLM uses a non-full-rank, or overparameterized, indicator variable approach to parameterization of linear models (instead of the full-rank reparameterization approach that is used in MANOVA). GLM uses a generalized inverse approach and uses the aliasing of redundant parameters to zero to allow greater flexibility in handling a variety of data situations, particularly situations involving empty cells. For features that are provided by GLM but unavailable in MANOVA, refer to General Linear Model (GLM) and MANOVA (GLM command).

To simplify the presentation, MANOVA reference material is divided into three sections: univariate designs with one dependent variable; multivariate designs with several interrelated dependent variables; and repeated measures designs in which the dependent variables represent the same types of measurements, taken at more than one time.

The full syntax diagram for MANOVA is presented here. The sections that follow include partial syntax diagrams that show the subcommands and specifications that are discussed in that section. Individually, those diagrams are incomplete. Subcommands that are listed for univariate designs are available for any analysis, and subcommands that are listed for multivariate designs can be used in any multivariate analysis, including repeated measures.

MANOVA was designed and programmed by Philip Burns of Northwestern University.