2024
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
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
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
Fisher, Z., & Crawford, C. (). Heterogeneity in Multiple-Subject Intensive Longitudinal Data: Leveraged Shared Information with Multi-Task Learning. International Meeting of the Psychometric Society.
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
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
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. (). 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.
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
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
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
Lipton, R., de la Garza, A., Wang, C., Derby, C., Katz, M., Oravecz, Z., Hakun, J., Sliwinski, M., & Ezzati, A. (). The Association of Blood-based biomarkers and Cognitive Change as Measured by Ecologically Sensitive Digital Biomarkers. Alzheimer's & Dementia, 19(0). https://doi.org/10.1002/alz.077999
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
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
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
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
Fisher, Z. (). Machine Learning for Multiple-Subject Time Series Analysis. Annual Meeting of the Society for Multivariate Experimental Psychology.
Merritt, S., Heshmati, S., Oravecz, Z., & Donaldson, S. (). Web of well-being: re-examining PERMA and subjective well-being through networks. Journal of Positive Psychology. https://doi.org/10.1080/17439760.2023.2209538
Hunter, M. (). State Space Mixture Modeling: Finding People with Similar Patterns of Change. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2023.2261224
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