Four New Corrected Statistics for SEM With Small Samples and Nonnormally Distributed Data
–Ge Jiang & Ke-Hai Yuan [Publisher] [Google Scholar]

Goodness of Fit in Item Factor Analysis: Effect of the Number of Response Alternatives
–Alberto Maydeu-Olivares, Amanda J. Fairchild & Alexander G. Hall [Publisher] [Google Scholar]

Mixture Simultaneous Factor Analysis for Capturing Differences in Latent Variables Between Higher Level Units of Multilevel Data | Open Access
–Kim De Roover, Jeroen K. Vermunt, Marieke E. Timmerman & Eva Ceulemans [Publisher] [Google Scholar]

Measurement Invariance Testing with Many Groups: A Comparison of Five Approaches
–Eun Sook Kim, Chunhua Cao, Yan Wang & Diep T. Nguyen [Publisher] [Google Scholar]

Examining and Controlling for Wording Effect in a Self-Report Measure: A Monte Carlo Simulation Study
–Honglei Gu, Zhonglin Wen & Xitao Fan [Publisher] [Google Scholar]

Effect Analysis Using Nonlinear Structural Equation Mixture Modeling
–Axel Mayer, Nora Umbach, Barbara Flunger & Augustin Kelava [Publisher] [Google Scholar]

Standardized Parameters in Misspecified Structural Equation Models: Empirical Performance in Point Estimates, Standard Errors, and Confidence Intervals
–Keke Lai & Xiaoguang Zhang [Publisher] [Google Scholar]

Fitting Structural Equation Model Trees and Latent Growth Curve Mixture Models in Longitudinal Designs: The Influence of Model Misspecification
–Satoshi Usami, Timothy Hayes & John McArdle [Publisher] [Google Scholar]

Evaluation of True Criterion Validity for Unidimensional Multicomponent Measuring Instruments in Longitudinal Studies
–Tenko Raykov & George A. Marcoulides [Publisher] [Google Scholar]

Teacher’s Corner

Multilevel Mediation With Small Samples: A Cautionary Note on the Multilevel Structural Equation Modeling Framework
–Daniel McNeish [Publisher] [Google Scholar]

Structural Models for Binary Repeated Measures: Linking Modern Longitudinal Structural Equation Models to Conventional Categorical Data Analysis for Matched Pairs
–Jason T. Newsom [Publisher] [Google Scholar]

Book Review

Review of Causal Inference in Statistics: A Primer, by Judea Pearl, Madelyn Glymour, and Nicholas P. Jewell
–Keith A. Markus [Publisher]

---