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Local Influence Analysis of Nonlinear Structural Equation Models

Published online by Cambridge University Press:  01 January 2025

Sik-Yum Lee  and
Nian-Sheng Tang
Sik-Yum Lee*
Affiliation:
The Chinese University of Hong Kong
Nian-Sheng Tang
Affiliation:
Yunnan University
*
Requests for reprints should be sent to: Prof. S.Y. Lee, Department of Statistics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. E-mail: sylee@sparc2.sta.cuhk.edu.hk.
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Abstract

By regarding the latent random vectors as hypothetical missing data and based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm, we investigate assessment of local influence of various perturbation schemes in a nonlinear structural equation model. The basic building blocks of local influence analysis are computed via observations of the latent variables generated by the Metropolis-Hastings algorithm, while the diagnostic measures are obtained via the conformal normal curvature. Seven perturbation schemes, including some perturbation schemes on latent vectors, are investigated. The proposed procedure is illustrated by a simulation study and a real example.

Keywords

Benchmarkconformal normal curvaturelocal influenceMetropolis-Hastings algorithmQ-displacement function

Information

Type
Theory And Methods
Information
Psychometrika , Volume 69 , Issue 4 , December 2004 , pp. 573 - 592
Copyright
Copyright © 2004 The Psychometric Society

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Footnotes

Acknowledgment: This research is fully supported by a grant (CUHK 4243/02H) from the Research Grant Council of the Hong Kong Special Administration Region. The authors are indebted to ICPSR and the relevant funding agency for allowing use of their data, and to the Editor and reviewers for their valuable comments for improving the paper.

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