2nd Edition Companion Files

The Handbook of SEM companion files are hosted on OSF. The links below will take you to an OSF file browser listing each chapter’s companion files, where you can download the entire set of companion files for a chapter or select individual files to view or download. If you select a file within the file browser, you will see options to download or view the file on the top bar of the file browser. To easily download all companion files for a chapter, navigate to that chapter’s page, select “OSF Storage (United States)” in the file browser, and you will see an option appear to “Download as zip,” providing you with all of that chapter’s companion files contained in a single ZIP file.

Chapter 4 – Visualizations for Structural Equation Modeling
Chapter 6 – Simulation Methods in Structural Equation Modeling
Chapter 11 – Model Selection in Structural Equation Modeling
Chapter 12 – Fitting Structural Equation Models with Missing Data
Chapter 13 – Structural Equation Modeling with the Mplus and lavaan Programs
Chapter 15 – Measurement Models with Categorical Indicators
Chapter 16 – Item Parceling in SEM: A Researcher Degree-of-Freedom Ripe for Opportunistic Use
Chapter 19 – Multitrait-Multimethod Models
Chapter 20 – Investigating Measurement Invariance Using Confirmatory Factor Analysis
Chapter 21 – Flexible Structural Equation Modeling Approaches for Analyzing Means
Chapter 22 – Mediation/Indirect Effects in Structural Equation Modeling
Chapter 23 – Latent Interaction Effects
Chapter 24 – Dynamic Moderation with Latent Interactions: General Cross-Lagged Panel Models with Interaction Effects Over Time
Chapter 25 – Psychometric Scale Evaluation Using Structural Equation Modeling and Latent Variable Modeling
Chapter 26 – Multilevel Structural Equation Modeling (files available soon)
Chapter 27 – Exploratory Structural Equation Modeling
Chapter 28 – Structural Equation Modeling with Small Samples and Many Variables
Chapter 30 – Latent Curve Modeling of Longitudinal Growth Data
Chapter 32 – Continuous-Time Dynamic Models
Chapter 33 – Latent Trait-State Models
Chapter 34 – Longitudinal Models for Assessing Dynamics in Dyadic Data
Chapter 35 – Structural Equation Modeling for Genetic Data
Chapter 36 – Structural Equation Modeling-Based Meta-Analysis
Chapter 37 – Nonlinear Structural Equation Models: Advanced Methods and Applications
Chapter 38 – Foundations and Extensions of Bayesian Structural Equation Modeling
Chapter 39 – Machine-Learning Approaches to Structural Equation Modeling