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
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
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.
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
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
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
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
Lombera, M., Lee, A., & Fisher, Z. (). Comparing Measurement Models of Childhood Maltreatment and Associations with Youth Psychological and Academic Functioning. ISPCAN.
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
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
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
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