ANOVA/MANOVA Quick Specs - Options Tab

Select the Options tab of the ANOVA/MANOVA Quick Specs dialog box to access the options described here.

Element Name Description
Sweep delta Enter the negative exponent for a base-10 constant delta (delta = 10-sdelta) in the Sweep delta field; the default value is 7. Delta is used (1) in sweeping, to detect redundant columns in the design matrix, and (2) for evaluating the estimability of hypotheses; specifically a value of 2*delta is used for the estimability check.
Inverse delta Enter the negative exponent for a base-10 constant delta (delta = 10-idelta) in the Inverse delta field; the default value is 12. Delta for matrix inversion is used to check for matrix singularity in matrix inversion calculations.
Parameterization Select the type of parameterization options you want to use for your general ANOVA/MANOVA model in the Parameterization group box.
Sigma-restricted Select the Sigma-restricted check box to compute the design matrix for categorical predictors in the model based on sigma-restricted coding; if it is not selected, the overparameterized model will be used. The sigma-restricted model is the default parameterization; see the GLM  Introductory Overview topic The Sigma-Restricted vs. Overparameterized Model for details.
No intercept Select the No intercept check box to exclude the intercept from the model.
Lack of fit Select the Lack of fit check box to compute the sums of squares for the pure error, i.e., the sums of squares within all unique combinations of values for the (categorical) predictor variables. On the ANOVA Results dialog box, options are available to test the lack-of-fit hypothesis. Note that in large designs with continuous predictors, the computations necessary to estimate the pure error can be very time consuming. See the GLM Introductory Overview topic Lack-of-Fit Tests Using Pure Error for a discussion of lack-of-fit tests and pure error; see also Experimental Design.
Cross-validation Click the Cross-validation button to display the Cross-Validation dialog box for specifying a categorical variable and a (code) value to identify observations that should be included in the computations for fitting the model (the analysis sample); all other observations with valid data for all predictor variables and dependent variables will automatically be classified as belonging to the validation sample (see the Residuals tab for a description of the available residual statistics for observations in the validation sample); note that all observations with valid data for all predictor variables but missing data for the dependent variables will automatically be classified as belonging to the prediction sample (see the Residuals tab topic for a description of available statistics for the prediction sample).
Sums of squares Select the method for constructing main effect and interaction hypotheses in unbalanced and incomplete designs in the Sums of squares group box. These methods are discussed in the GLM  Introductory Overview. For the sigma-restricted model the default value is Type VI (unique or effective hypothesis decomposition; see Hocking, 1985) and Type IV is not valid; for the overparameterized model the default value is Type III (orthogonal; see Goodnight, 1980), and Type VI is not valid.

For alternative ways of specifying designs in ANOVA/MANOVA, see Methods for Specifying Designs.