Fin
31
Conclusion
Dyadic Structural Equation Modeling in R
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Preface
License and Supporting this Open-Access Book
About the Author
Acknowledgements
Act I: Getting Started
1
Introduction
2
The Big Picture
3
Dyadic Data Structure
4
Latent Variables in SEM
Act II: SEM Fundamentals
5
Models (and Their Elements)
6
Model Identification and Scale-Setting
7
Estimating Dyadic SEMs: Common Practices, Problems, and Solutions
8
Model Fit Indexes
9
Model Comparison Strategies
10
A Simple (Non-Dyadic) Example in {lavaan}
Intermission 1: Meet Your Dyadic Models
11
Design, Scope, and Form of Dyadic Models
Act III: Uni-Construct Cross-Sectional Dyadic Models
12
The One-Factor (Surprinslgy Dyadic) Model
13
The Correlated Two-Factor Model
14
The Bifactor Model
15
The Hierarchical Factor Model
16
The Causal Relations Between Univariate Cross-Sectional Dyadic SEMs
17
Dyadic Invariance Testing in Univariate Cross-Sectional Dyadic SEMs
18
Choosing Between Uni-Construct Cross-Sectional Dyadic Models
Act IV: Bi-Construct Cross-Sectional Dyadic Models
19
The Couple Interdependence Model
20
The Actor-Partner Interdependence Model
21
The Bifactor Structural Model
22
The Common Fate Model
23
Mixing Univariate Structures in Bivariate Models
Intermission 2: What Is ‘(In)distinguishability’?
24
(In)distinguishability Is More Complicated than You Think
Act V: Advanced Applications of Dyadic SEM
25
“Third Variable” Cross-Sectional Dyadic Models
26
Multi-Group Cross-Sectional Dyadic Models
27
Longitudinal Dyadic Models
28
Dyadic Exploratory Factor Analysis
29
Monte Carlo Simulations of Dyadic Modeling Strategies
30
Contributing to Open-Source Software Development for Dyadic SEM (and Beyond)
Fin
31
Conclusion
References
Appendices
A
A Review of Sufficient
R
for Dyadic SEM
Fin
31
Conclusion
31
Conclusion
30
Contributing to Open-Source Software Development for Dyadic SEM (and Beyond)
References