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TOC: Struct Equation Modeling

Introduction

Structural Equation Modeling: A Multidisciplinary Journal, 21(1)

BIC and Alternative Bayesian Information Criteria in the Selection of Structural Equation Models
Kenneth A. Bollen, Jeffrey J. Harden, Surajit Ray & Jane Zavisca [] []

Latent Growth Curve Model Selection: The Potential of Individual Case Residuals
Tenko Raykov & Spiridon Penev [] []

Measurement Bias in Multilevel Data
Suzanne Jak, Frans J. Oort & Conor V. Dolan [] []

The Robustness of ME/I Evaluations to Among-Group Dependence
Brian L. Perdomo, L. Allison Jones-Farmer, Bryan D. Edwards & Daniel Svyantek [] []

A Structural Equation Multidimensional Scaling Model for One-Mode Asymmetric Dissimilarity Data
J. Fernando Vera & Chiristian D. Rivera [] []

Sufficient Sample Sizes for Discrete-Time Survival Analysis Mixture Models
Mirjam Moerbeek [] []

Additive Models for Multitrait–Multimethod Data With a Multiplicative Trait–Method Relationship: A Simulation Study
Lidong Zhang, Rong Jin, Walter L. Leite & James Algina [] []

Modeling Configural Patterns in Latent Variable Profiles: Association With an Endogenous Variable
Mark L. Davison, Yu-Feng Chang & Ernest C. Davenport Jr. [] []

Model Specification for Latent Interactive and Quadratic Effects in Matrix Form
Shu-Ping Chen & Chung-Ping Cheng [] []

Relative Performance of Categorical Diagonally Weighted Least Squares and Robust Maximum Likelihood Estimation
Deborah L. Bandalos [] []

Are Method Effects Permanent or Ephemeral in Nature? The Case of the Revised Life Orientation Test
Michele Vecchione, Guido Alessandri, Gian Vittorio Caprara & John Tisak [] []

Teacher’s Corner

On Fitting a Multivariate Two-Part Latent Growth Model
Shu Xu, Shelley A. Blozis & Elizabeth A. Vandewater [] []

Understanding Robust Corrections in Structural Equation Modeling
Victoria Savalei [] []

Book Review

Restoring Causal Analysis to Structural Equation ModelingReview of Causality: Models, Reasoning, and Inference (2nd Edition), by Judea Pearl
Stephen G. West & Tobias Koch []


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