SPSS® 12.0 Command Syntax Reference

652 GLM: Univariate
Temporary variables (tempvar) are:
PRED, WPRED, RESID, WRESID, DRESID, ZRESID, SRESID, SEPRED, COOK, LEVER
Example
Overview
Options
GLM YIELD BY SEED FERT
/DESIGN.
This section describes the use of GLM for univariate analyses. However, most of the subcommands
described here can be used in any type of analysis with GLM. For additional subcommands
used in those types of analysis, see GLM: Multivariate and GLM: Repeated
Measures. For basic specification, syntax rules, and limitations of the GLM procedures, see
GLM: Overview.
Design Specification. You can specify which terms to include in the design on the DESIGN
subcommand. This allows you to estimate a model other than the default full factorial model,
incorporate factor-by-covariate interactions or covariate-by-covariate interactions, and indicate
nesting of effects.
Contrast Types. You can specify contrasts other than the default deviation contrasts on the
CONTRAST subcommand.
Optional Output. You can choose from a wide variety of optional output on the PRINT subcommand.
Output appropriate to univariate designs includes descriptive statistics for each cell,
parameter estimates, Levene’s test for equality of variance across cells, partial eta-squared
for each effect and each parameter estimate, the general estimable function matrix, and a
contrast coefficients table (L’ matrix). The OUTFILE subcommand allows you to write out the
covariance or correlation matrix, the design matrix, or the statistics from the betweensubjects
ANOVA table into a separate SPSS data file.
Using the EMMEANS subcommand, you can request tables of estimated marginal means
of the dependent variable and their standard deviations. The SAVE subcommand allows you
to save predicted values and residuals in weighted or unweighted and standardized or
unstandardized forms. You can specify different means comparison tests for comparing all
possible pairs of cell means using the POSTHOC subcommand. In addition, you can specify
your own hypothesis tests by specifying an L matrix and a K matrix to test the univariate
hypothesis LB = K.