Abstract
A general approach to the analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed. Several different types of covariance structures are considered as special cases of the general model. These include models for sets of congeneric tests, models for confirmatory and exploratory factor analysis, models for estimation of variance and covariance components, regression models with measurement errors, path analysis models, simplex and circumplex models. Many of the different types of covariance structures are illustrated by means of real data.
Keywords
CovarianceMathematicsMatérn covariance functionCovariance intersectionEstimation of covariance matricesCovariance functionLaw of total covarianceCovariance and correlationPath analysis (statistics)Covariance matrixStatisticsRational quadratic covariance functionAnalysis of covarianceExploratory factor analysisRegression analysisEconometricsCorrelationStructural equation modelingRandom variableMultivariate random variableSum of normally distributed random variables
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Publication Info
- Year
- 1978
- Type
- article
- Volume
- 43
- Issue
- 4
- Pages
- 443-477
- Citations
- 1000
- Access
- Closed
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Cite This
Karl G. Jöreskog
(1978).
Structural Analysis of Covariance and Correlation Matrices.
Psychometrika
, 43
(4)
, 443-477.
https://doi.org/10.1007/bf02293808
Identifiers
- DOI
- 10.1007/bf02293808