2023

Chow, S., Losardo, D., Park, J., & Molenaar, P. (). Continuous-Time Dynamic Models: Connections to Structural Equation Models and Other Discrete-Time Models: Structural Equation Modeling: Concepts, Issues, and Applications. , 2.
Chow, S., Nahum-Shani, I., Baker, J., Spruijt-Metz, D., Allen, N., Auerbach, R., Dunton, G., Friedman, N., Intille, S., Klasnja, P., Marlin, B., Nock, M., Rauch, S., Pavel, M., Vrieze, S., Wetter, D., Kleiman, E., Brick, T., Perry, H., Wolff-Hughes, D., et al (). The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols. Translational Behavioral Medicine, 13(1), 7-16. https://doi.org/10.1093/tbm/ibac069

2022

Petrie, D., Fisher, Z., & Geier, C. (). Examining the Influence of Training on the Balance Between Goal-Directed and Habitual Control using Time-varying GAM Models in Adolescents and Young Adults.: The International Congress for Integrative Developmental Cognitive Neuroscience (Flux). .
Bollen, K., Fisher, Z., Brehm, C., Lilly, A., Luo, L., & Ye, A. (). Fifty Years of Structural Equation Models (SEMs): A History of Generalization, Unification, and Diffusion.. Social Science Review, 107, 40. https://doi.org/10.1016/j.ssresearch.2022.102769
Bollen, K., Fisher, Z., Lilly, A., Brehm, C., Luo, L., Martinez, A., & Ye, A. (). Fifty years of structural equation modeling: A history of generalization, unification, and diffusion. Social Science Research, 107. https://doi.org/10.1016/j.ssresearch.2022.102769
Lee, T., Fisher, Z., & Gatkze-Kopp, L. (). Performance Monitoring and its Development – A Cognitive Systems Approach.. Psychophysiology, 58(51).
Fisher, Z., Kim, Y., Fredrickson, B., & Pipiras, V. (). Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data. Psychometrika, 87(2), 1-29. https://doi.org/10.1007/s11336-021-09825-7
Luo, L., Fisher, Z., Arizmendi, C., Molenaar, P., Beltz, A., & Gates, K. (). Estimating Both Directed and Undirected Contemporaneous Relations in Time Series Data Using Hybrid-Group Iterative Multiple Model Estimation. Psychological Methods, 28(1), 189-206. https://doi.org/10.1037/met0000485
Mascherek, A., Weber, S., Riebandt, K., Cassanello, C., Leicht, G., Brick, T., Gallinat, J., & Kühn, S. (). On the relation between a green and bright window view and length of hospital stay in affective disorders. Psychiatrie et Psychobiologie, 65(1). https://doi.org/10.1192/j.eurpsy.2022.9
Heshmati, S., & Oravecz, Z. (). I feel loved when other people feel loved: Cultural congruence in beliefs on love is related to well-being. Journal of Social and Personal Relationships, 39(2), 347-371. https://doi.org/10.1177/02654075211036510
Van Doren, Natalia, , Van Doren, N., Oravecz, Z., Soto, J., & Roeser, R. (). Examining the Cultural Consensus on Beliefs About Mindfulness Among US College-Attending Young Adults. Mindfulness, 13(10), 2420-2433. https://doi.org/10.1007/s12671-022-01956-x
Fredman, S., Fischer, M., Baucom, D., Le, Y., Taverna, E., Chow, S., Ram, N., & Marshall, A. (). PTSD Symptom Cluster Severity Predicts Momentary Emotion Dynamics During Couple Conversations. Behavior Therapy. https://doi.org/10.1016/j.beth.2022.09.004
Strayhorn, J., Collins, L., Brick, T., Marchese, S., Pfammatter, A., Pellegrini, C., & Spring, B. (). Using factorial mediation analysis to better understand the effects of interventions. Translational Behavioral Medicine, 12(1), 84-89. https://doi.org/10.1093/tbm/ibab137
Chow, S., Lee, J., Chow, J., Hofman, A., van der Maas, H., van der Maas, Han L. J., , Pearl, D., Chow, S., Chow, S., Molenaaar, P., Molenaar, P., & Molenaar, Peter C. M., (). Control Theory Forecasts of Optimal Training Dosage to Facilitate Children’s Arithmetic Learning in a Digital Educational Application. Psychometrika, 87(2), 559-592. https://doi.org/10.1007/s11336-021-09829-3
Boker, S., Timo, v., von Oertzen, T., Pritikin, J., Hunter, M., Brick, T., Brandmeier, A., Brandmaier, A., & Neale, M. (). Products of Variables in Structural Equation Models. Structural Equation Modeling, 30(5), 708-718. https://doi.org/10.1080/10705511.2022.2141749
Li, Y., Li, , Oravecz, Z., Zhou, S., Barnett, I., Bodovski, Y., Zhou, S., Chow, S., Bodovski, Y., Barnett, I., Friedman, N., Chi, G., Barnett, I., Zhou, Y., Chow, S., S., Zhou, Y., Friedman, N., Vrieze, Scott, I, , Vrieze, S., et al (). Bayesian Forecasting with a Regime-Switching Zero-Inflated Multilevel Poisson Regression Model: An Application to Adolescent Alcohol Use with Spatial Covariates. Psychometrika, 87(2), 376-402. https://doi.org/10.1007/s11336-021-09831-9