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Structural equation models with continuous and polytomous variables
Authors:Sik-Yum Lee  Wai-Yin Poon  P. M. Bentler
Affiliation:(1) University of California, Los Angeles;(2) Department of Statistics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Abstract:A two-stage procedure is developed for analyzing structural equation models with continuous and polytomous variables. At the first stage, the maximum likelihood estimates of the thresholds, polychoric covariances and variances, and polyserial covariances are simultaneously obtained with the help of an appropriate transformation that significantly simplifies the computation. An asymptotic covariance matrix of the estiates is also computed. At the second stage, the parameters in the structural covariance model are obtained via the generalized least squares approach. Basic statistical properties of the estimates are derived and some illustrative examples and a small simulation study are reported.This research was supported in part by a research grant DA01070 from the U. S. Public Health Service. We are indebted to several referees and the editor for very valuable comments and suggestions for improvement of this paper. The computing assistance of King-Hong Leung and Man-Lai Tang is also gratefully acknowledged.
Keywords:structural equation models  polychoric correlations  polyserial correlations  maximum likelihood  generalized least squares  asymptotic properties
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