2023
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
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
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
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
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
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.
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
Fisher, Z. (). Machine Learning for Multiple-Subject Time Series Analysis. Annual Meeting of the Society for Multivariate Experimental Psychology.
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
Park, J., Fisher, Z., Chow, S., P., Molenaar PCM, , & Molenaar, P. (). Evaluating Discrete Time Methods for Subgrouping Continuous Processes. Multivariate Behavioral Research, 1-13. https://doi.org/10.1080/00273171.2023.2235685
Gates, K., Chow, S., & Molenaar, P. (). Intensive Longitudinal Analysis of Human Processes. . https://doi.org/10.1201/9780429172649
Hunter, M. (). State Space Mixture Modeling: Finding People with Similar Patterns of Change. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2023.2261224
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., 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
Ollero, M., Estrada, E., Hunter, M., & Cáncer, P. (). Characterizing Affect Dynamics With a Damped Linear Oscillator Model: Theoretical Considerations and Recommendations for Individual-Level Applications. Psychological Methods. https://doi.org/10.1037/met0000615
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
Shenk, C., Shores, K., Ram, N., Felt, J., Felt, J., Chimed-Ochir, U., Olson, A., & Fisher, Z. (). Contamination in Observational Research on Child Maltreatment: A Conceptual and Empirical Review With Implications for Future Research. Child Maltreatment, 10775595231224472. https://doi.org/10.1177/10775595231224472
Park, J., Park, J., Fisher, Z., Chow, S., Molenaar PCM, , & Molenaar, P. (). On Subgrouping Continuous Processes in Discrete Time. Multivariate Behavioral Research, 58(1), 154-155. https://doi.org/10.1080/00273171.2022.2160957
Park, J., Chow, S., Epskamp, S., & Molenaar, P. (). Subgrouping with Chain Graphical VAR Models. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2023.2289058
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.
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).