MODEL dependent-variables = independent-effects;
The MODEL statement names the dependent variables and independent effects. If one or more MANOVA or REPEATED statements are specified, then multiple dependent variables define a multivariate model. In the absence of the MANOVA and REPEATED statements, a univariate model is assumed, and multiple dependent variables represent different scenarios for the cell means.
The independent-effects can involve classification variables, continuous variables, or both. You can include main effects and interactions by using the effects notation of PROC GLM; for more information, see the section Specification of Effects in ChapterĀ 46: The GLM Procedure. For any model effect that involves classification variables (main effects and interactions), the number of levels cannot exceed 32,767. If no independent effects are specified, only an intercept term is fit. You can specify only one MODEL statement, and it must appear before the POWER statement if the EFFECTS= option is specified in the POWER statement.
For a univariate model, you can account for covariates without specifying them explicitly in the model by using the NCOVARIATES= option and either the CORRXY= or PROPVARREDUCTION= option in the POWER statement. For a multivariate model, you must explicitly specify any covariates in the MODEL statement.
The values of dependent variables in the exemplary data set (the data set named by the DATA= option in the PROC GLMPOWER statement) are surmised response means across subject profiles. For a univariate model, multiple dependent variables correspond to multiple scenarios for these cell means.
The MODEL statement is required. You can specify only one MODEL statement.