Factor Analysis Descriptives
Statistics. Univariate descriptives includes 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 of 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.
To Specify Descriptive Statistics and Correlation Coefficients
This feature requires Statistics Base Edition.
- From the menus choose:
- In the Factor Analysis dialog box, click Descriptives.