User Guide

447
Factor Analysi
s
Factor Analy
sis Descriptives
Figure 29-4
Factor Analysis Descriptives dialog box
Statistics. Univariate statistics include the mean, standard deviation, and number
of valid cases for each variable. Initial solution displays initial communalities,
eigenvalues, and the percentage of variance explained.
Correlation Matrix. The available options are coefficients, significance levels,
determinant, KMO and Bartlett’s test of sphericity, inverse, reproduced, and
anti-image.
 KMO and Bartlett's Test o f Sphericity. The Kaiser-Meyer-Olkin measure of
sampling adequacy tests whether the partial correlations among variables are
small. Bartlett's test of sphericity tests whether the correlation matrix is an
identity matrix, which would indicate that the factor model is inappropriate.
 Reproduced. The estimated correlation matrix from the factor solution. Residuals
(difference between estimated and observed correlations) are also displayed.
 Anti-image. The anti-image correlation matrix contains the negatives of the
partial correlation coefficients, and the anti-image covariance matrix contains
the negatives of the partial covariances. In a good factor model, most of the
off-diagonal elements will be small. The measure of sampling adequacy for a
variable is displayed on the diagonal of the anti-image correlation matrix.