SPSS® 12.0 Command Syntax Reference

Multiple Classification Analysis
ANOVA 135
STATISTICS=MCA displays the MCA, the Factor Summary, and the Model Goodness of Fit
tables.
• The MCA table presents counts, predicted means, and deviations of predicted means from
the grand mean for each level of each factor. The predicted and deviation means each
appear in up to three forms: unadjusted, adjusted for other factors, and adjusted for other
factors and covariates.
• The Factor Summary table displays the correlation ratio (eta) with the unadjusted
deviations (the square of eta indicates the proportion of variance explained by all
categories of the factor), a partial beta equivalent to the standardized partial regression
coefficient that would be obtained by assigning the unadjusted deviations to each factor
category and regressing the dependent variable on the resulting variables, and the parallel
partial betas from a regression that includes covariates in addition to the factors.
• The Model Goodness of Fit table shows R and R 2 for each model.
• The tables cannot be produced if METHOD is omitted or if METHOD=UNIQUE. When produced,
the MCA table does not display values adjusted for factors if COVARIATES is omitted,
if COVARIATES=FIRST, or if COVARIATES=WITH and METHOD=EXPERIMENTAL. A full
MCA table is produced only if METHOD=HIERARCHICAL or if METHOD=EXPERIMENTAL
and COVARIATES=AFTER.
MISSING Subcommand
By default, a case that has a missing value for any variable named in the analysis list is deleted
for all analyses specified by that list. Use MISSING to include cases with user-missing data.
EXCLUDE Exclude cases with missing data. This is the default.
INCLUDE Include cases with user-defined missing data.
References
Andrews, F., J. Morgan, J. Sonquist, and L. Klein. 1973. Multiple classification analysis. 2nd ed.
Ann Arbor: University of Michigan.