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Zhang, Zhiyong; Wang, Lijuan – Psychometrika, 2013
Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including list wise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum…
Descriptors: Maximum Likelihood Statistics, Structural Equation Models, Simulation, Measurement Techniques
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de la Torre, Jimmy – Psychometrika, 2011
The G-DINA ("generalized deterministic inputs, noisy and gate") model is a generalization of the DINA model with more relaxed assumptions. In its saturated form, the G-DINA model is equivalent to other general models for cognitive diagnosis based on alternative link functions. When appropriate constraints are applied, several commonly used…
Descriptors: Structural Equation Models, Identification, Models, Comparative Analysis
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Lee, Sik-Yum; Xia, Ye-Mao – Psychometrika, 2008
In this paper, normal/independent distributions, including but not limited to the multivariate t distribution, the multivariate contaminated distribution, and the multivariate slash distribution, are used to develop a robust Bayesian approach for analyzing structural equation models with complete or missing data. In the context of a nonlinear…
Descriptors: Structural Equation Models, Bayesian Statistics, Evaluation Methods, Evaluation Research
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Lee, Sik-Yum; Song, Xin-Yuan – Psychometrika, 2003
Proposed a new nonlinear structural equation model with fixed covariates to deal with some complicated substantive theory and developed a Bayesian path sampling procedure for model comparison. Illustrated the approach with an illustrative example using data from an international study. (SLD)
Descriptors: Bayesian Statistics, Comparative Analysis, Sampling, Structural Equation Models
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Lee, Sik-Yum – Psychometrika, 2006
A Bayesian approach is developed for analyzing nonlinear structural equation models with nonignorable missing data. The nonignorable missingness mechanism is specified by a logistic regression model. A hybrid algorithm that combines the Gibbs sampler and the Metropolis-Hastings algorithm is used to produce the joint Bayesian estimates of…
Descriptors: Mathematics, Structural Equation Models, Bayesian Statistics, Goodness of Fit
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Hoshino, Takahiro; Kurata, Hiroshi; Shigemasu, Kazuo – Psychometrika, 2006
In the behavioral and social sciences, quasi-experimental and observational studies are used due to the difficulty achieving a random assignment. However, the estimation of differences between groups in observational studies frequently suffers from bias due to differences in the distributions of covariates. To estimate average treatment effects…
Descriptors: Structural Equation Models, Simulation, Social Sciences, Computation
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Lee, Sik-Yum; Xia, Ye-Mao – Psychometrika, 2006
By means of more than a dozen user friendly packages, structural equation models (SEMs) are widely used in behavioral, education, social, and psychological research. As the underlying theory and methods in these packages are vulnerable to outliers and distributions with longer-than-normal tails, a fundamental problem in the field is the…
Descriptors: Maximum Likelihood Statistics, Statistical Distributions, Structural Equation Models, Robustness (Statistics)