SPSS® 12.0 Command Syntax Reference

128 ANOVA
Methods for Decomposing Sums of Squares. By default, the regression approach (keyword
UNIQUE) is used. You can request the classic experimental or hierarchical approach using the
METHOD subcommand.
Statistical Display. Using the STATISTICS subcommand, you can request means and counts for
each dependent variable for groups defined by each factor and each combination of factors up
to the fifth level. You also can request unstandardized regression coefficients for covariates
and multiple classification analysis (MCA) results, which include the MCA table, the Factor
Summary table, and the Model Goodness of Fit table. The MCA table shows treatment
effects as deviations from the grand mean and includes a listing of unadjusted category effects
for each factor, category effects adjusted for other factors, and category effects adjusted for all
factors and covariates. The Factor Summary table displays eta and beta values. The Goodness
of Fit table shows R and R 2 for each model.
Basic Specification
• The basic specification is a single VARIABLES subcommand with an analysis list. The
minimum analysis list specifies a list of dependent variables, the keyword BY, a list of factor
variables, and the minimum and maximum integer values of the factors in parentheses.
• By default, the model includes all interaction terms up to five-way interactions. The sums
of squares are decomposed using the regression approach, in which all effects are assessed
simultaneously, with each effect adjusted for all other effects in the model. A case that has
a missing value for any variable in an analysis list is omitted from the analysis.
Subcommand Order
• The analysis list must be first if the keyword VARIABLES is omitted from the specification.
• The remaining subcommands can be named in any order.
Operations
A separate analysis of variance is performed for each dependent variable in an analysis list,
using the same factors and covariates.
Limitations
• Maximum 5 analysis lists.
• Maximum 5 dependent variables per analysis list.
• Maximum 10 factor variables per analysis list.
• Maximum 10 covariates per analysis list.
• Maximum 5 interaction levels.
• Maximum 25 value labels per variable displayed in the MCA table.
• The combined number of categories for all factors in an analysis list plus the number of
covariates must be less than the sample size.