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Lee, Sik-Yum; Song, Xin-Yuan; Cai, Jing-Heng – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Analysis of ordered binary and unordered binary data has received considerable attention in social and psychological research. This article introduces a Bayesian approach, which has several nice features in practical applications, for analyzing nonlinear structural equation models with dichotomous data. We demonstrate how to use the software…
Descriptors: Bayesian Statistics, Structural Equation Models, Computer Software, Computation
Song, Xin-Yuan; Lee, Sik-Yum; Hser, Yih-Ing – Structural Equation Modeling: A Multidisciplinary Journal, 2009
In longitudinal studies, investigators often measure multiple variables at multiple time points and are interested in investigating individual differences in patterns of change on those variables. Furthermore, in behavioral, social, psychological, and medical research, investigators often deal with latent variables that cannot be observed directly…
Descriptors: Medical Research, Structural Equation Models, Longitudinal Studies, Multivariate Analysis
Song, Xin-Yuan; Lee, Sik-Yum – Structural Equation Modeling: A Multidisciplinary Journal, 2008
Structural equation models are widely appreciated in behavioral, social, and psychological research to model relations between latent constructs and manifest variables, and to control for measurement errors. Most applications of structural equation models are based on fully observed data that are independently distributed. However, hierarchical…
Descriptors: Psychological Studies, Life Satisfaction, Job Satisfaction, Structural Equation Models

Song, Xin-Yuan; Lee, Sik-Yum; Zhu, Hong-Tu – Structural Equation Modeling, 2001
Studied the maximum likelihood estimation of unknown parameters in a general LISREL-type model with mixed polytomous and continuous data through Monte Carlo simulation. Proposes a model selection procedure for obtaining good models for the underlying substantive theory and discusses the effectiveness of the proposed model. (SLD)
Descriptors: Maximum Likelihood Statistics, Monte Carlo Methods, Selection, Simulation
Song, Xin-Yuan; Lee, Sik-Yum – Structural Equation Modeling: A Multidisciplinary Journal, 2006
Structural equation models are widely appreciated in social-psychological research and other behavioral research to model relations between latent constructs and manifest variables and to control for measurement error. Most applications of SEMs are based on fully observed continuous normal data and models with a linear structural equation.…
Descriptors: Structural Equation Models, Maximum Likelihood Statistics, Item Response Theory, Error of Measurement
Lee, Sik-Yum; Song, Xin-Yuan; Lee, John C. K. – Journal of Educational and Behavioral Statistics, 2003
The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among latent variables with fully observed data. However, in social and behavioral sciences, nonlinear relationships among the latent variables are important for establishing more meaningful models…
Descriptors: Structural Equation Models, Simulation, Computer Software, Computation
Song, Xin-Yuan; Lee, Sik-Yum – Multivariate Behavioral Research, 2006
In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…
Descriptors: Structural Equation Models, Bayesian Statistics, Markov Processes, Monte Carlo Methods
Song, Xin-Yuan; Lee, Sik-Yum – Multivariate Behavioral Research, 2005
In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal effects among the latent variables, the structural equation in the model is defined by a nonlinear function. The basic idea of the…
Descriptors: Structural Equation Models, Simulation, Computation, Error of Measurement