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Structural Modeling and Psychometrika: An Historical Perspective on Growth and Achievements

Published online by Cambridge University Press:  01 January 2025

P. M. Bentler
P. M. Bentler*
Affiliation:
University of California, Los Angeles
*
Requests for reprints should be sent to P. M. Benfler, Department of Psychology, Franz Hall, University of California, 405 Hilgard Avenue, Los Angeles, CA 90024.
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Abstract

The field of linear structural equation modeling with continuous variables is reviewed. Trends in psychometric theory and data analysis across the five decades of publication of Psychometrika are discussed, especially the clarification of concepts of population and sample, explication of the parametric structure of models, delineation of concepts of exploratory and confirmatory data analysis, expansion of statistical theory in psychometrics, estimation via optimization of an explicit objective function, and implementation of general function minimization methods. Developments in the ideas of factor analysis, latent variables, as well as structural and causal modeling are noted. Some major conceptual achievements involving general covariance structure representations, multiple population models, and moment structures are reviewed. The major statistical achievements of normal theory generalized least squares estimation, elliptical and distribution-free estimation, and higher-moment estimation are discussed. Computer programs that implement some of the theoretical developments are described.

Type
50th Anniversary Section
Information
Psychometrika , Volume 51 , Issue 1 , March 1986 , pp. 35 - 51
Copyright
Copyright © 1986 The Psychometric Society

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Footnotes

This review was supported in part by USPHS grants DA00017 and DA01070.

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