Abstract
Structural models for covariance matrices are used when studying relationships between variables and are employed predominantly in the social sciences. The best known of these is the factor analysis model but recently there has been rapid development of extensions and alternatives. Most of this work has appeared in psychometric journals. Textbooks on applied multivariate analysis are recently including chapters on factor analysis. They tend, however, to be out of date and give little attention to modern developments such as efficient computational methods in maximum likelihood factor analysis, effective methods for oblique rotation, methods for obtaining standard errors of factor loadings and extensions of the factor analysis model.
Keywords
CovarianceFactor (programming language)Oblique caseFactor analysisAnalysis of covarianceMultivariate statisticsEconometricsRotation (mathematics)Computer scienceMathematicsStatisticsArtificial intelligenceLinguistics
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Publication Info
- Year
- 1982
- Type
- book-chapter
- Pages
- 72-141
- Citations
- 398
- Access
- Closed
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Cite This
Michael W. Browne
(1982).
COVARIANCE STRUCTURES.
Cambridge University Press eBooks
, 72-141.
https://doi.org/10.1017/cbo9780511897375.003
Identifiers
- DOI
- 10.1017/cbo9780511897375.003