Abstract
It is assumed that observations on a set of variables have a multivariate normal distribution with a general parametric form of the mean vector and the variance-covariance matrix. Any parameter of the model may be fixed, free or constrained to be equal to other parameters. The free and constrained parameters are estimated by maximum likelihood. A wide range of models is obtained from the general model by imposing various specifications on the parametric structure of the general model. Examples are given of areas and problems, especially in the behavioural sciences, where the method may be useful.
Keywords
MathematicsCovarianceParametric statisticsMultivariate normal distributionCovariance matrixRange (aeronautics)Applied mathematicsMultivariate statisticsStatisticsParametric modelGeneral covarianceSet (abstract data type)Variance (accounting)Multivariate analysis of varianceAnalysis of covarianceComputer science
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Publication Info
- Year
- 1970
- Type
- article
- Volume
- 57
- Issue
- 2
- Pages
- 239-251
- Citations
- 1116
- Access
- Closed
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Cite This
Karl G. Jöreskog
(1970).
A general method for analysis of covariance structures.
Biometrika
, 57
(2)
, 239-251.
https://doi.org/10.1093/biomet/57.2.239
Identifiers
- DOI
- 10.1093/biomet/57.2.239