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TOC: Struct Equation Modeling

Introduction

Structural Equation Modeling: A Multidisciplinary Journal, 21(2)

Evaluating Model Fit With Ordered Categorical Data Within a Measurement Invariance Framework: A Comparison of Estimators
Daniel A. Sass, Thomas A. Schmitt & Herbert W. Marsh [] []

A Simulation Study Comparing Recent Approaches for the Estimation of Nonlinear Effects in SEM Under the Condition of Nonnormality
Holger Brandt, Augustin Kelava & Andreas Klein [] []

Modeling Change in the Presence of Nonrandomly Missing Data: Evaluating a Shared Parameter Mixture Model
Nisha C. Gottfredson, Daniel J. Bauer & Scott A. Baldwin [] []

The Impact of Ignoring Time Series Processes in Linear Growth Mixture Modeling
Namwook Koo & Walter L. Leite [] []

Comparing Squared Multiple Correlation Coefficients Using Structural Equation Modeling
Joyce L. Y. Kwan & Wai Chan [] []

The Impact of Inaccurate “Informative” Priors for Growth Parameters in Bayesian Growth Mixture Modeling
Sarah Depaoli [] []

An Empirical Evaluation of Mediation Effect Analysis With Manifest and Latent Variables Using Markov Chain Monte Carlo and Alternative Estimation Methods
Jinsong Chen, Jaehwa Choi, Brandi A. Weiss & Laura Stapleton [] []

Determining the Number of Latent Classes in Single- and Multiphase Growth Mixture Models
Su-Young Kim [] []

Robust Two-Stage Approach Outperforms Robust Full Information Maximum Likelihood With Incomplete Nonnormal Data
Victoria Savalei & Carl F. Falk [] []

Dyadic Curve-of-Factors Model: An Introduction and Illustration of a Model for Longitudinal Nonexchangeable Dyadic Data
Tiffany A. Whittaker, S. Natasha Beretvas & Toni Falbo [] []

Examining Measure Correlations With Incomplete Data Sets
Tenko Raykov, Brooke C. Schneider, George A. Marcoulides & Peter A. Lichtenberg [] []

Book Review

Review of Data Analysis With MPlus, by Christian Geiser
Pega Davoudzadeh []