Fitting structural equation models using estimating equations: A model segregation approach

Authors: Yuan K-H.¹; Chan W.²

Source: British Journal of Mathematical and Statistical Psychology, Volume 55, Number 1, May 2002 , pp. 41-62(22)

Publisher: British Psychological Society

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Abstract:

Problems such as improper solution, non-convergence, subsets of variables having different distribution, and latent variables with single indicators are common in the practice of structural equation modelling. In such cases, it may be feasible to fix some model parameters at prespecified values while concentrating on estimating some other parameters. This paper formulates such a model fitting process through a model segregation approach. The statistical properties of this procedure are studied using the theory of estimating equations and optimal estimating functions. The dependency of the new parameter estimates on those of the prespecified parameter estimates is characterized for several commonly used estimating equations. A rescaled model fit statistic is proposed. Examples illustrate various applications of this procedure.

Language: English

Document Type: Research article

Affiliations: 1: University of Notre Dame, USA 2: The Chinese University of Hong Kong, Hong Kong

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