Monte Carlo Simulation Power Analysis Using Mplus and R (Paperback, 1)

I. Cross-Sectional Power Analyses
1. Introduction
- Statement of the Problem: Statistical Power in the Empirical Literature
- What Does This Mean?
- Why Monte Carlo Simulation Power Analyses?
- Software to Conduct Power Analyses
- Why Use the Approach Shown in This Book?
- Proof of Concept: Why and How the Assumption of Standardization Simplifies
- A Relationship Research Question Power Analysis
- Mplus Monte Carlo Power Analysis: Bivariate Regression
- R Monte Carlo Power Analysis: Bivariate Regression using lavaan and simsem
- A Comparison Research Question Power Analysis
- Mplus Monte Carlo Power Analysis: Two-Group Comparison
- R Monte Carlo Power Analysis: Two-Group Comparison
- Conclusion
- Suggested Readings & Resources
- Appendix 1.1: Chapter Addendum: The Fundamentals
2. A Multivariate, Two-Group, Pretest-Posttest Power Analysis
- Mplus Monte Carlo Power Analysis: Multivariate Two-Group Comparison
- R Monte Carlo Power Analysis: Multivariate Two-Group Comparison
- Simulation Power Analysis Write-Up: Multivariate Two-Group Comparison
- Suggested Readings
3. Path Analysis
- Mplus Monte Carlo Power Analysis: Mediated Path Analysis
- R Monte Carlo Power Analysis: Mediated Path Analysis
- Simulation Power Analysis Write-Up: Mediated Path Analysis
- Suggested Readings
4. Structural Equation Model
- Measurement Model: CFA
- SEM: Predictive Relationships Among CFA Models
- R Code for SEM Model-Reproduced Correlation Matrix
- Mplus Monte Carlo Power Analysis: SEM
- R Monte Carlo Power Analysis: SEM
- Impacts of Unreliability on SEM Power Estimates
- Mplus Syntax for Lower Reliability SEM Power Analysis
- R Syntax for Lower Reliability SEM Power Analysis
- Simulation Power Analysis Write-Up: SEM
- Suggested Readings
5. Logistic Regression
- The Logistical Foundation: Probabilities, Odds and Log Odds (Logits)
- Logistic Regression Power Analysis: Vakhitova and Alston-Knox (2018)
- Mplus Monte Carlo Power Analysis: Logistic Regression
- Simulation Power Analysis Write-Up: Logistic Regression
- Problems Using R packages lavaan or simsem for Logistic Regression Power Analysis
- Suggested Readings
6. Missing Data in Monte Carlo Simulation Power Analyses
- Missing Data in Mplus
- Missing Data in R Using simsem and lavaan Packages
- A Univariate Example of MCAR
- A Simple Regression MAR Example
- Monte Carlo Simulation Power Estimates and Missing Data
- Multivariate Two-Group Power Analysis Using Mplus
- Multivariate Two-Group Power Analysis Using R
- Multivariate Two-Group Simulation Power Analysis with Missing Data Write-Up
- Structural Equation Model
- Structural Equation Model Power Analysis Using Mplus
- Structural Equation Model Power Analysis Using R
- Structural Equation Model Simulation Power Analysis with Missing Data Write-Up
- Missing Data Concluding Remarks
- Suggested Readings
II. Longitudinal Power Analyses
7. Unconditional Latent Growth Curve
- The Metric of Time: Scaling and Centering
- An Unconditional Latent Growth Curve Model Power Analysis
- Mplus Monte Carlo Simulation Power Analysis
- R Monte Carlo Simulation Power Analysis
- Unconditional Latent Growth Curve Model Simulation Power Analysis Write-Up
- Latent Growth Curve Models: Moving Forward
- Suggested Readings
8. Time-Invariant Covariates
- A Tauber et al. (2021) Replication Power Analysis
- Mplus Monte Carlo Power Analysis: Longitudinal RCT Pilot
- R Monte Carlo Power Analysis: Longitudinal RCT Pilot
- Longitudinal RCT Pilot Model Simulation Power Analysis Write-Up
- But, What Ifa€|?
- Mplus Monte Carlo Power Analysis: Longitudinal Treatment Effect
- R Monte Carlo Power Analysis: Longitudinal Treatment Effect
- Longitudinal RCT Treatment Effect Model Simulation Power Analysis Write-Up
- Ok, BUTa€|?
- Mplus Monte Carlo Power Analysis: Longitudinal RCT Covariate
- R Monte Carlo Power Analysis: Longitudinal RCT Covariate Issues
- Longitudinal RCT Covariate Simulation Power Analysis Write-Up
- Just One More Thing
- Mplus Monte Carlo Power Analysis: Longitudinal RCT Moderation Model
- R Monte Carlo Power Analysis: Longitudinal RCT Moderation Model Issues
- Longitudinal RCT Moderation Model Simulation Power Analysis Write-Up
- A Final Note
- Suggested Readings
- Appendix 8.1: a€œOld Schoola€? Power Analyses Using a€œOld Schoola€? Methods
- Mixed-Factorial ANOVA Design Matrices
- A Mixed-Factorial ANOVA Model Simulation Power Analysis Write-Up
9. Adding Time-Varying Covariates
- Mplus Monte Carlo Power Analysis: Adding Time-Varying Covariates
- R Monte Carlo Power Analysis: Adding Time-Varying Covariates Issues
- Longitudinal Time-Varying Covariates Simulation Power Analysis Write-Up
- Mplus Monte Carlo Power Analysis: A Random Effect Model
- R Monte Carlo Power Analysis: Random Effect Model Issues
- Longitudinal Random Effect Model Simulation Power Analysis Write-Up
- Suggested Readings
10. Parallel-Process Mediation
- A Parallel-Process Power Analysis Based on Becker et al. (2016)
- Mplus Monte Carlo Power Analysis for Parallel-Process Mediation
- R Monte Carlo Power Analysis for Parallel-Process Mediation
- Parallel-Process Simulation Power Analysis Write-Up
- Suggested Readings
11. Power Analysis for Complex Longitudinal Designs
- A Complex Longitudinal Power Analysis Based on Beal et al. (2020)
- Maltreatment Predicting CDI Trajectory Variance
- CDI Trajectory and Maltreatment Predict Quality of Life (QOL)
- CDI Trajectory and Maltreatment Predict Biomarkers
- Logistic Prediction of Opioid Use Disorder
- Prediction of Opioid Misuse Disorder
- Assembling the Mplus Syntax
- A Note on RSyntax for this Design
- Complex Longitudinal Simulation Power Analysis Write-Up
- Suggested Readings
III. Conclusion
12. Statistical Power in a a€œPost-p < .05a€? World
- Ringing the Alarm Bell
- Possible Paths Toward a a€œPost-p < .05a€? World
- What Does All of This Mean?
- Suggested Readings
References
Author Index
Subject Index
About the Author

Online-Only Appendices:
Appendix A. Statistical Power for Latent Variable Moderation
Appendix B. Part 1: Statistical Power for Survival Analysis
Appendix B. Part 2: Continuous-Time Survival Analysis
Appendix C. Monte Carlo Simulation Power for Two-Level Models (Arend and Schafer, 2019)
Appendix D. Statistical Power for Moderated Mediation