Abstract
The assumptions of the model for factor analysis do not exclude a class of indeterminate covariances between factors and error variables (Grayson, 2003). The construction of all factors of the model for factor analysis is generalized to incorporate indeterminate factor-error covariances. A necessary and sufficient condition is given for indeterminate factor-error covariances to be arbitrarily small, for mean square convergence of the regression predictor of factor scores, and for the existence of a unique determinate factor and error variable. The determinate factor and error variable are uncorrelated and satisfy the defining assumptions of factor analysis. Several examples are given to illustrate the results.
| Original language | English |
|---|---|
| Pages (from-to) | 503-519 |
| Journal | Psychometrika. Vol 67(1) |
| Volume | 71 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 7 Aug 2006 |
Keywords
- common factor analysis
- confirmatory factor analysis
- factor indeterminacy
Research Focus Areas Hanze University of Applied Sciences * (mandatory by Hanze)
- Healthy Ageing
Research Focus Areas Research Centre or Centre of Expertise * (mandatory by Hanze)
- Frailty and adequate care
Publinova themes
- Other
- Health