Volume 59, Issue 4, 2024
1. Methodological and Statistical Practices of Using Symptom Networks to Evaluate Mental Health Interventions: A Review and Reflections
Lea Schumacher, Julian Burger, Jette Echterhoff & Levente Kriston
2. Understanding Composite-Based Structural Equation Modeling Methods From the Perspective of Regression Component Analysis
Edward E. Rigdon
3. Understanding the Consequences of Collinearity for Multilevel Models: The Importance of Disaggregation Across Levels
Haley E. Yaremych & Kristopher J. Preacher
4. Bayesian Analysis of Multi-Factorial Experimental Designs Using SEM
Benedikt Langenberg, Jonathan L. Helm & Axel Mayer
5. Network Inference With the Lasso
Lourens Waldorp & Jonas Haslbeck
6. A Confidence Interval for the Difference Between Standardized Regression Coefficients
Samantha F. Anderson
7. Exploring Within-Person Variability in Qualitative Negative and Positive Emotional Granularity by Means of Latent Markov Factor Analysis
Marcel C. Schmitt, Leonie V. D. E. Vogelsmeier, Yasemin Erbas, Simon Stuber & Tanja Lischetzke
8. Finite Mixtures of Latent Trait Analyzers With Concomitant Variables for Bipartite Networks: An Analysis of COVID-19 Data
Dalila Failli, Maria Francesca Marino & Francesca Martella
9. Counterfactual Mediation Analysis with a Latent Class Exposure
Gemma Hammerton, Jon Heron, Katie Lewis, Kate Tilling & Stijn Vansteelandt
10. Considering the ‘With Whom’: Differences Between Event- and Signal-Contingent ESM Data of Person-Specific Social Interactions
Marie Stadel, Marijtje A. J. van Duijn, Aidan G. C. Wright, Laura F. Bringmann & Timon Elmer
11. Bayesian Multivariate Logistic Regression for Superiority and Inferiority Decision-Making under Observable Treatment Heterogeneity
Xynthia Kavelaars, Joris Mulder & Maurits Kaptein
12. Using Monte Carlo Simulation to Forecast the Scientific Utility of Psychological App Studies: A Tutorial
Sebastian Kueppers, Richard Rau & Florian Scharf