Search results for author:"Sik-Yum Lee"
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A Bayesian Approach for Analyzing Hierarchical Data with Missing Outcomes through Structural Equation Models
Structural Equation Modeling: A Multidisciplinary Journal Vol. 15, No. 2 (April 2008) pp. 272–300
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...
Journal of Educational and Behavioral Statistics Vol. 28, No. 2 (2003) pp. 111–134
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,...
Bayesian Methods for Analyzing Structural Equation Models with Covariates, Interaction, and Quadratic Latent Variables
Structural Equation Modeling: A Multidisciplinary Journal Vol. 14, No. 3 (2007) pp. 404–434
The analysis of interaction among latent variables has received much attention. This article introduces a Bayesian approach to analyze a general structural equation model that accommodates the general nonlinear terms of latent variables and...
A Bayesian Approach for Nonlinear Structural Equation Models with Dichotomous Variables Using Logit and Probit Links
Structural Equation Modeling: A Multidisciplinary Journal Vol. 17, No. 2 (2010) pp. 280–302
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...