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June, 1988 The Asymptotic Normal Distribution of Estimators in Factor Analysis under General Conditions
T. W. Anderson, Yasuo Amemiya
Ann. Statist. 16(2): 759-771 (June, 1988). DOI: 10.1214/aos/1176350834

Abstract

Asymptotic properties of estimators for the confirmatory factor analysis model are discussed. The model is identified by restrictions on the elements of the factor loading matrix; the number of restrictions may exceed that required for identification. It is shown that a particular centering of the maximum likelihood estimator derived under assumed normality of observations yields an asymptotic normal distribution that is common to a wide class of distributions of the factor vectors and error vectors. In particular, the asymptotic covariance matrix of the factor loading estimator derived under the normal assumption is shown to be valid for the factor vectors containing a fixed part and a random part with any distribution having finite second moments and for the error vectors consisting of independent components with any distributions having finite second moments. Thus the asymptotic standard errors of the factor loading estimators computed by standard computer packages are valid for virtually any type of nonnormal factor analysis. The results are extended to certain structural equation models.

Citation

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T. W. Anderson. Yasuo Amemiya. "The Asymptotic Normal Distribution of Estimators in Factor Analysis under General Conditions." Ann. Statist. 16 (2) 759 - 771, June, 1988. https://doi.org/10.1214/aos/1176350834

Information

Published: June, 1988
First available in Project Euclid: 12 April 2007

zbMATH: 0646.62051
MathSciNet: MR947576
Digital Object Identifier: 10.1214/aos/1176350834

Subjects:
Primary: 62H25
Secondary: 62E20

Rights: Copyright © 1988 Institute of Mathematical Statistics

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Vol.16 • No. 2 • June, 1988
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