User Guide

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Chapter 28

Univariate ANOVAs. Performs a one-way analysis of variance test for equality of
group means
for each independent variable.
 Box's M. Ate
st for the equality of the group covariance matrices. For sufficiently
large samples, a nonsignificant p value means there is insufficient evidence that
the matrices differ. The test is sensitive to departures from multivariate normality.
Function Coefficients. Available options are Fisher’s classification coefficients and
unstandard
ized coefficients.
 Fisher's.
Displays Fisher's classification function coefficients that can be used
directly for classification. A set of coefficients is obtained for each group, and a
case is assigned to the group for which it has the largest discriminant score.
 Unstandardized. Displays the unstandardized discriminant function coefficients.
Matrices. Available matrices of coefficients for independent variables are
within-gr
oups correlation matrix, within-groups covariance matrix, separate-groups
covariance matrix, and total covariance matrix.
 Within-groups correlation. Displays a pooled within-groups correlation matrix that
is obtaine
d by averaging the separate covariance matrices for all groups before
computing the correlations.
 Within-groups covariance. Displays a pooled within-groups covariance matrix,
which may differ from the total covariance matrix. The matrix is obtained by
averagin
g the separate covariance matrices for all groups.
 Separat
e-groups covariance.
Displays separate covariance matrices for each
group.
 Total covariance. Displays a covariance matrix from all cases as if they were
from a single sample.