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
Losardo, D., Chow, S., Panter, A., Burkley, M., & Burkley, E. (). Ecological Momentary Assessment (EMA) Designs with Planned Missingness. , 657-698. https://doi.org/10.1007/978-3-031-56318-8_26
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
Park, J., Fisher, Z., Hunter, M., Shenk, C., Russell, M., Molenaar, P., & Chow, S. (). Unsupervised Model Construction in Continuous-Time. Structural Equation Modeling, 32(3), 377-399. https://doi.org/10.1080/10705511.2024.2429544
Fisher, Z., & Crawford, C. (). Are General Truths Only Generally True? Accommodating Qualitative Heterogeneity in Individual-Level Dynamics using Multi-VAR. Association for Psychological Science Annual Meeting 2024.
Freet, C., Evans, B., Brick, T., Deneke, E., Wasserman, E., Ballard, S., Stankoski, D., Kong, L., Raja-Khan, N., Nyland, J., Others, , Arnold, A., Krishnamurthy, V., Fernandez-Mendoza, J., Cleveland, H., Scioli, A., Molchanow, A., Messner, A., Ayaz, H., Grigson, P., et al (). Ecological momentary assessment and cue-elicited drug craving as primary endpoints: study protocol for a randomized, double-blind, placebo-controlled clinical trial testing the efficacy of a GLP-1 receptor agonist in opioid use disorder. Addiction Science and Clinical Practice, 19(1), 56. https://doi.org/10.1186/s13722-024-00481-7
Boker, S., Brick, T., Fisher, Z., Hunter, M., Rosseel, Y., & Neale, M. (). Paths to the future: A panel discussion of the future of SEM. International Meeting of the Psychometric Society.
Losardo, D., Chow, S., Panter, A., Burkley, M., & Burkley, E. (). Ecological momentary assessment (EMA) designs with planned missingness. Springer Proceedings in Mathematics & Statistics: Dependent Data in Social Sciences Research. , 2, 657-698.
Chow, S., Hamaker, E., & Ram, N. (). From Behavioral Genetics to Idiographic Science: Methodological Developments and Applications Inspired by the Work of Peter C. M. Molenaar. Multivariate Behavioral Research, 59(6), 1107-1110. https://doi.org/10.1080/00273171.2024.2394054
Fatimah, H., Hunter, M., & Bornovalova, M. (). Modeling the Dynamics of Addiction Relapse via the Double-Well Potential System. Journal of Psychopathology and Clinical Science. https://doi.org/10.1037/abn0000960
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
Henry, T., Fisher, Z., & Bollen, K. (). Optimal Instrument Selection Using Bayesian Model Averaging for Model Implied Instrumental Variable Two Stage Least Squares Estimators. Structural Equation Modeling. https://doi.org/10.1080/10705511.2024.2343926
Felt, J., Chimed-Ochir, U., Shores, K., Olson, A., Yanling, Y., Li, Y., Fisher, Z., Ram, N., & Shenk, C. (). Contamination bias in the estimation of child maltreatment causal effects on adolescent internalizing and externalizing behavior problems. Journal of Child Psychology and Psychiatry and Allied Disciplines, 10. https://doi.org/10.1111/jcpp.13990
Cho, Y., Chow, S., Marini, C., & Martire, L. (). Multilevel Latent Differential Structural Equation Model with Short Time Series and Time-Varying Covariates: A Comparison of Frequentist and Bayesian Estimators. Multivariate Behavioral Research, 59(5), 934-956. https://doi.org/10.1080/00273171.2024.2347959
Lombera, M., Lee, A., & Fisher, Z. (). Comparing Measurement Models of Childhood Maltreatment and Associations with Youth Psychological and Academic Functioning. ISPCAN.
Ellis, O., Oravecz, Z., & Heshmati, S. (). What Makes Early Adults Feel Loved? Cultural Consensus of Felt Love Experiences in Early Adulthood. Applied Developmental Science, 28(2), 161–177. https://doi.org/10.1080/10888691.2022.2158086
Park, J., Chow, S., & Molenaar, P. (). What the fuzz: Dependent Data in Social Sciences Research. Springer Proceedings in Mathematics & Statistics. , 2, 161-180.
Apsley, H., Lancaster, J., Ren, W., Brick, T., & Cleveland, H. (). Experiences at recovery community centers predict holistic recovery outcomes: a daily diary assessment of RCC helpfulness, meaningfulness, and recovery identity. Frontiers in Public Health, 12. https://doi.org/10.3389/fpubh.2024.1476441
Park, J., Chow, S., & Molenaar, P. (). What the Fuzz!? Leveraging Ambiguity in Dynamic Network Models. , 161-180. https://doi.org/10.1007/978-3-031-56318-8_7
Apsley, H., Ren, W., Lancaster, J., Brick, T., & Cleveland, H. (). Recovery Community Center Visits and Activities: A Description Using a Daily Diary Approach. Alcoholism Treatment Quarterly, 43(1), 3-12. https://doi.org/10.1080/07347324.2024.2415595
Li, Y., Oravecz, Z., Ji, L., & Chow, S. (). Multiple Imputation with Factor Scores: A Practical Approach for Handling Simultaneous Missingness Across Items in Longitudinal Designs. Multivariate Behavioral Research, 60(1), 61-89. https://doi.org/10.1080/00273171.2024.2371816
Ellis, O., Heshmati, S., & Oravecz, Z. (). What makes early adults feel loved? Cultural consensus of felt love experiences in early adulthood. Applied Developmental Science, 28(2), 161-177. https://doi.org/10.1080/10888691.2022.2158086
Fisher, Z., & Crawford, C. (). Heterogeneity in Multiple-Subject Intensive Longitudinal Data: Leveraged Shared Information with Multi-Task Learning. International Meeting of the Psychometric Society.
Garrison, S., Hunter, M., Lyu, X., Trattner, J., & Burt, S. (). BGmisc: An R Package for Extended Behavior Genetics Analysis. Journal of Open Source Software, 9, 1-4. https://doi.org/10.21105/joss.06203
2023
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