2024
Li, Y., Williams, L., Muth, C., Heshmati, S., Chow, S., & Oravecz, Z. (). A Growth of Hierarchical Autoregression Model for Capturing Individual Differences in Changes of Dynamic Characteristics of Psychological Processes. Structural Equation Modeling. https://doi.org/10.31234/osf.io/vr3ce
Martinez, G., Maggs, J., Bámaca, M., Fisher, Z., & Robins, R. (). Prospective Associations Between Stressors and Alcohol Use From Early Adolescence to Young Adulthood in Mexican-Origin Youth in the United States. Developmental Psychology. https://doi.org/10.1037/dev0001877
Heshmati, S., Muth, C., Roeser, R., Smyth, J., Jamalabadi, H., & Oravecz, Z. (). Conceptualizing psychological well-being as a dynamic process: Implications for research on mobile health interventions. Social and Personality Psychology Compass, 18(1). https://doi.org/10.1111/spc3.12933
2023
Heshmati, S., Kibrislioglu Uysal, N., Kim, S., Oravecz, Z., & Donaldson, S. (). Momentary PERMA: An Adapted Measurement Tool for Studying Well-Being in Daily Life. Journal of Happiness Studies, 24(8), 2441-2472. https://doi.org/10.1007/s10902-023-00684-w
Rhubart, D., & Santos, A. (). Research Note Showing That the Rural Mortality Penalty Varies by Region, Race, and Ethnicity in the United States, 1999–2016. Demography, 60(6), 1699-1709. https://doi.org/10.1215/00703370-11078239
Ou, L., Hunter, M., Lu, Z., Stifter, C., & Chow, S. (). Estimation of nonlinear mixed-effects continuous-time models using the continuous-discrete extended Kalman filter. British Journal of Statistical Psychology, 76(3), 462-490. https://doi.org/10.1111/bmsp.12318
Long, J., Pritschet, S., Keller, K., Cheah, C., Boot, L., Klippel, A., Brick, T., Edwards, C., Rolls, B., & Masterson, T. (). Portion size affects food selection in an immersive virtual reality buffet and is related to measured intake in laboratory meals varying in portion size. Appetite, 191(107052). https://doi.org/10.1016/j.appet.2023.107052
Ahn, Y., Önal Ertuğrul, I., Chow, S., Cohn, J., & Messinger, D. (). Automated measurement of infant and mother Duchenne facial expressions in the Face-to-Face/Still-Face. Infancy, 28(5), 910-929. https://doi.org/10.1111/infa.12556
Luong, G., Miller, J., Kirkland, D., Morse, J., Wrzus, C., Diehl, M., Chow, S., & Riediger, M. (). Valuing negative affect weakens affect-health linkages: similarities and differences across affect valuation measures. Motivation and Emotion, 47(3), 347-363. https://doi.org/10.1007/s11031-023-10012-7
Fisher, Z., Parsons, J., Gates, K., & Hopfinger, J. (). Blind Subgrouping of Task-based fMRI. Psychometrika, 88(2), 434-455. https://doi.org/10.1007/s11336-023-09907-8
Luo, L., Fisher, Z., Molenaar, P., Beltz, A., & Kathleen, G. (). Estimating Both Directed and Bidirectional Contemporaneous Relations in Time Series Data Using Hybrid-GIMME.. Psychological Methods.
Santos-Lozada, A. (). Trends in deaths from falls among adults aged 65 years or older in the US, 1999-2020. JAMA, 329(18), 1605-1607. https://doi.org/10.1001%2Fjama.2023.3054
Hunter, M., Pritikin, J., Kirkpatrick, R., & Neale, M. (). Rethinking Ordinal Variable Identification in Weighted Least Squares Structural Equation Modeling. PsyArXiv, 1-81. https://doi.org/10.31234/osf.io/mnc7q
Van Doren, N., Oravecz, Z., Soto, J., & Roeser, R. (). Correction to: Examining the Cultural Consensus on Beliefs About Mindfulness Among US College-Attending Young Adults (Mindfulness, (2022), 13, 10, (2420-2433), 10.1007/s12671-022-01956-x). Mindfulness, 14(3), 761. https://doi.org/10.1007/s12671-023-02081-z
Olson, A., Chow, S., Jones, D., & Shenk, C. (). Child maltreatment, parent-child relationship quality, and parental monitoring in relation to adolescent behavior problems: Disaggregating between and within person effects. Child Abuse and Neglect, 136, 106003. https://doi.org/10.1016/j.chiabu.2022.106003
Gunther, K., Anaya, B., Fisher, Z., Jones, M., Petrie, D., Hlutkowsky, C., & Perez-Edgar, K. (). A Person-Centered, Network-Based Approach to Mother-Infant Neural Synchrony with Functional Near Infrared Spectroscopy: Society for Research on Child Development Biennial Meeting. .
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.
Chen, M., Chen, M., Chow, S., Oravecz, Z., & Ferrer, E. (). Fitting Bayesian Stochastic Differential Equation Models with Mixed Effects through a Filtering Approach. Multivariate Behavioral Research, 58(5), 1014-1038. https://doi.org/10.1080/00273171.2023.2171354
Fisher, Z., Kim, Y., Pipiras, V., Crawford, C., Petrie, D., Hunter, M., & Geier, C. (). Structured Estimation of Heterogeneous Time Series. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2023.2283837
Pearce, A., & Brick, T. (). Validation of computational models to characterize cumulative intake curves from video-coded meals. Frontiers in Nutrition, 10(1088053). https://doi.org/10.3389/fnut.2023.1088053
Ji, L., Li, Y., Potter, L., Lam, C., Nahum-Shani, I., Wetter, D., & Chow, S. (). Multiple imputation of missing data in multilevel ecological momentary assessments: an example using smoking cessation study data. Frontiers in Digital Health, 5. https://doi.org/10.3389/fdgth.2023.1099517
Jin, C., Osotsi, A., & Oravecz, Z. (). Predicting Adolescent Female Stress with Wearable Device Data Using Machine and Deep Learning. . https://doi.org/10.1109/BSN58485.2023.10331414
Fisher, Z. (). Machine Learning for Multiple-Subject Time Series Analysis. Annual Meeting of the Society for Multivariate Experimental Psychology.
Shenk, C., Olson, A., Olson, A., Dunning, E., Dunning, E., Shores, K., Ram, N., Fisher, Z., Felt, J., Chimed-Ochir, U., & Chimed-Ochir, U. (). Addressing Contamination Bias in Child Maltreatment Research: Innovative Methods for Enhancing the Accuracy of Causal Estimates: Innovative Methods in Child Maltreatment Research and Practice. . https://doi.org/10.1007/978-3-031-33739-0_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