Structural Equation Models with Continuous and Polytomous Variables

Sik‐Yum Lee · Wai‐Yin Poon · Peter M. Bentler

123 citations0/0 files storedPsychometrika

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Psychometric Methodologies and Testing Statistical Methods and Applications Statistical Methods and Bayesian Inference

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 estimates 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.

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References

1989EQS : structural equations program manual 1989LISREL 7 : a guide to the program and applications 1984A General Structural Equation Model with Dichotomous, Ordered Categorical, and Continuous Latent Variable Indicators 1984The Effect of Sampling Error on Convergence, Improper Solutions, and Goodness-of-Fit Indices for Maximum Likelihood Confirmatory Factor Analysis 1984Asymptotically distribution‐free methods for the analysis of covariance structures 1985Nonconvergence, Improper Solutions, and Starting Values in Lisrel Maximum Likelihood Estimation 1970Fitting a Response Model for n Dichotomously Scored Items 1978Contributions to Factor Analysis of Dichotomous Variables

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