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The Analysis of Structural Equation Models by Means of Derivative Free Nonlinear Least Squares

Published online by Cambridge University Press:  01 January 2025

Sik-Yum Lee  and
Robert I. Jennrich
Sik-Yum Lee*
Affiliation:
The Chinese University of Hong Kong
Robert I. Jennrich
Affiliation:
University of California, Los Angeles
*
Requests for reprints should be sent to Dr. Sik-Yum Lee, Department of Statistics, The Chinese University of Hong Kong, Shatin, N, T., Hong Kong.
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Abstract

It is shown that the PAR Derivative-Free Nonlinear Regression program in BMDP can be used to fit structural equation models, producing generalized least squares estimates, standard errors, and goodness-of-fit test statistics. Covariance structure models more general than LISREL can be analyzed. The approach is particularly useful for dealing with new non-standard models and experimenting with alternate methods of estimation.

Keywords

generalized least squaresstandard errorgoodness-of-fit statisticsHeywood solutioncovariance structure models
Type
Original Paper
Information
Psychometrika , Volume 49 , Issue 4 , December 1984 , pp. 521 - 528
Copyright
Copyright © 1984 The Psychometric Society

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Footnotes

The research of the second author was supported by the NSF grant MCS 83-01587.

We wish to thank our referees for some very valuable suggestions.

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