2020
Park, J., Park, J., Chow, S., Chow, S., Fisher, Z., & Molenaar, P. (). Affect and Personality: Ramifications of Modeling (Non-)Directionality in Dynamic Network Models. European Journal of Psychological Assessment, 36(6), 1009-1023. https://doi.org/10.1027/1015-5759/a000612
Fisher, Z., & Bollen, K. (). An Instrumental Variable Estimator for Mixed Indicators: Analytic Derivatives and Alternative Parameterizations. Psychometrika, 85(3), 660-683. https://doi.org/10.1007/s11336-020-09721-6
Oravecz, Z., & Vandekerckhove, J. (). A joint model of consensus and change over time. Journal of Mathematical Psychology, 98.
Oravecz, Z., & Vandekerckhove, J. (). A joint process model of consensus and longitudinal dynamics. Journal of Mathematical Psychology, 98. https://doi.org/10.1016/j.jmp.2020.102386
Brick, T., & Bailey, D. (). Rock the MIC: The Matrix of Implied Causation, a Tool for Experimental Design and Model Checking. Advances in Methods and Practices in Psychological Science, 3(3), 286-299. https://doi.org/10.1177/2515245920922775
Liu, C., Ji, L., Chow, S., Kang, B., Leve, L., Shaw, D., Ganiban, J., Natsuaki, M., Reiss, D., & Neiderhiser, J. (). Child Effects on Parental Negativity: The Role of Heritable and Prenatal Factors. Child Development, 91(5), e1064-e1081. https://doi.org/10.1111/cdev.13404
Hilpert, P., Brick, T., Flückiger, C., Vowels, M., Ceulemans, E., Kuppens, P., & Sels, L. (). What can be learned from couple research: Examining emotional co-regulation processes in face-to-face interactions. Journal of Counseling Psychology, 67(4), 475-487. https://doi.org/10.1037/cou0000416
Brick, T., Mundie, J., Weaver, J., Fraleigh, R., & Oravecz, Z. (). Low-burden mobile monitoring, intervention, and real-time analysis using the wear-IT framework: example and usability study. JMIR Formative Research, 4(6). https://doi.org/10.2196/16072
Ji, L., Chen, M., Oravecz, Z., Cummings, E., Lu, Z., & Chow, S. (). A Bayesian Vector Autoregressive Model with Nonignorable Missingness in Dependent Variables and Covariates: Development, Evaluation, and Application to Family Processes. Structural Equation Modeling, 27(3), 442-467. https://doi.org/10.1080/10705511.2019.1623681
Booij, S., Wigman, J., Jacobs, N., Thiery, E., Derom, C., Wichers, M., & Oravecz, Z. (). Cortisol dynamics in depression: Application of a continuous-time process model. Psychoneuroendocrinology, 115. https://doi.org/10.1016/j.psyneuen.2020.104598
Lei, Z., Hung, H., Lee, W., Yang, D., Shen, C., & Chow, S. (). Efficient Algorithms towards Network Intervention. The Web Conference 2020 (WWW ’20), 2021, 2021-2031. https://doi.org/10.1145/3366423.3380269
Gates, K., Fisher, Z., & Bollen, K. (). Latent variable GIMME using model implied instrumental variables (MIIVs). Psychological Methods, 25(2), 227-242. https://doi.org/10.1037/met0000229
Oravecz, Z., Dirsmith, J., Heshmati, S., Vandekerckhove, J., & Brick, T. (). Psychological well-being and personality traits are associated with experiencing love in everyday life. Personality and Individual Differences, 153. https://doi.org/10.1016/j.paid.2019.109620
Dunton, G., Wang, S., Ponnada, A., Campo, R., Chow, S., & Intille, S. (). INNOVATIVE ECOLOGICAL MOMENTARY ASSESSMENT STRATEGIES TO CAPTURE MICRO-TEMPORAL PROCESSES UNDERLYING LONG-TERM CHANGES IN PHYSICAL ACTIVITY, SEDENTARY BEHAVIOR, AND SLEEP. ANNALS OF BEHAVIORAL MEDICINE, 54, S146-S146.
Heshmati, S., Heshmati, S., Oravecz, Z., Brick, T., & Roeser, R. (). Assessing psychological well-being in early adulthood: Empirical evidence for the structure of daily well-being via network analysis. Applied Developmental Science, 26(2), 207-225. https://doi.org/10.1080/10888691.2020.1766356
Fisher, Z., Chow, S., Molenaar, P., Molenaar, Peter C. M., , Fredrickson, B., Pipiras, V., & Gates, K. (). A Square-Root Second-Order Extended Kalman Filtering Approach for Estimating Smoothly Time-Varying Parameters. Multivariate Behavioral Research, 57(1), 134-152. https://doi.org/10.1080/00273171.2020.1815513
Chen, M., Chow, S., Hammal, Z., Messinger, D., Cohn, J., Cohn, J., & Messinger, D. (). A Person- and Time-Varying Vector Autoregressive Model to Capture Interactive Infant-Mother Head Movement Dynamics. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2020.1762065
Mundie, J., Weaver, J., Oravecz, Z., & Brick, T. (). Wear-IT Smartphone App and Framework. .
Leonard, K., Evans, B., Evans, M., Oravecz, Z., Smyth, J., & Downs, D. (). Effect of Technology-Supported Interventions on Prenatal Gestational Weight Gain, Physical Activity, and Healthy Eating Behaviors: a Systematic Review and Meta-analysis. Journal of Technology in Behavioral Science, 6(1), 25-41. https://doi.org/10.1007/s41347-020-00155-6
You, D., Hunter, M., Chen, M., & Chow, S. (). A Diagnostic Procedure for Detecting Outliers in Linear State-Space Models. MULTIVARIATE BEHAVIORAL RESEARCH, 55(2), 231-255. https://doi.org/10.1080/00273171.2019.1627659
Fisher, Z. (). Robust Estimation and Dynamic Models. .
Shewark, E., Shewark, E., Brick, T., & Buss, K. (). Capturing temporal dynamics of fear behaviors on a moment-to-moment basis. Infancy, 25(3), 264-285. https://doi.org/10.1111/infa.12328
Knapp, K., Brick, T., Bunce, S., Bunce, S., Brick, T., Deneke, E., & Cleveland, H. (). Daily associations among craving, affect, and social interactions in the lives of patients during residential opioid use disorder treatment.. Psychology of Addictive Behaviors. https://doi.org/10.1037/adb0000612
Husmann, K., Brick, T., & Estabrook, R. (). mxmmod: Measurement Model of Derivatives in OpenMx. .
Osotsi, A., Osotsi, A., Oravecz, Z., Li, Q., Smyth, J., & Brick, T. (). Individualized Modeling to Distinguish Between High and Low Arousal States Using Physiological Data. Journal of Healthcare Informatics Research, 4(1), 91--109. https://doi.org/10.1007/s41666-019-00064-1