Abstract
In order to study the effectiveness of factor analytic methods, a procedure was developed for computing simulated correlation matrices which are more similar to real data correlation matrices than are those matrices computed from the factor analysis structural model. In the present investigation, three methods of factor extraction were studied as applied to 54 simulated correlation matrices which varied in proportion of variance derived from a major factor domain, number of factors in the major domain, and closeness of the simulation procedure to the factor analysis structural model. While the factor extraction methods differed little from one another in quality of results for matrices more dissimilar to the factor analytic model, major differences in quality of results were associated with fewer factors in the major domain, higher proportion of variance from the major domain, and closeness of the simulation procedure to the factor analysis structural model.
Keywords
ClosenessCorrelationVariance (accounting)Factor analysisStatisticsFactor (programming language)Domain (mathematical analysis)MathematicsComputer scienceMathematical analysisGeometry
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Publication Info
- Year
- 1969
- Type
- article
- Volume
- 34
- Issue
- 4
- Pages
- 421-459
- Citations
- 284
- Access
- Closed
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Cite This
Ledyard R Tucker,
Raymond F. Koopman,
Robert L. Linn
(1969).
Evaluation of Factor Analytic Research Procedures by means of Simulated Correlation Matrices.
Psychometrika
, 34
(4)
, 421-459.
https://doi.org/10.1007/bf02290601
Identifiers
- DOI
- 10.1007/bf02290601