2025
Lyu, X., Burt, S., Hunter, M., Good, R., Carroll, S., & Garrison, S. (). Detecting mtDNA Effects with an Extended Pedigree Model: An Analysis of Statistical Power and Estimation Bias. Behavior Genetics, 55(4), 320-337. https://doi.org/10.1007/s10519-025-10225-1
Petrie, D., Knapp, K., Freet, C., Deneke, E., Stankoski, D., Brick, T., Cleveland, H., & Bunce, S. (). Contemporaneous link between pain and craving in patients recovering from opioid use disorder during residential treatment. Substance Use and Misuse, 60(7), 978-988. https://doi.org/10.1080/10826084.2025.2478590
Das, J., Ji, L., Shen, Y., Kumara, S., Buxton, O., & Chow, S. (). Performance evaluation of a machine learning-based methodology using dynamical features to detect nonwear intervals in actigraphy data in a free-living setting. Sleep Health, 11(2), 166-173. https://doi.org/10.1016/j.sleh.2024.10.003
Blahošová, J., Tancoš, M., Cho, Y., Šmahel, D., Elavsky, S., Chow, S., & Lebedíková, M. (). Examining the Reciprocal Relationship Between Social Media Use and Perceived Social Support Among Adolescents: A Smartphone Ecological Momentary Assessment Study. Media Psychology, 28(1), 70-101. https://doi.org/10.1080/15213269.2024.2310834
Noll, J., Felt, J., Russotti, J., Guastaferro, K., Day, S., & Fisher, Z. (). Rates of Population-Level Child Sexual Abuse After a Community-Wide Preventive Intervention. A.M.A. American journal of diseases of children. https://doi.org/10.1001/jamapediatrics.2024.6824
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, 32(2), 237-250. https://doi.org/10.1080/10705511.2024.2402328
Oravecz, Z., Sliwinski, M., Kim, S., Williams, L., Katz, M., & Vandekerckhove, J. (). Partially Observable Predictor Models for Identifying Cognitive Markers. Computational Brain and Behavior, 8(3), 410-420. https://doi.org/10.1007/s42113-025-00238-8
Skurka, C., Troy, C., Yang, Y., Smith, R., Tornello, S., Rosenberger, J., Brick, T., & Myrick, J. (). “It is in the Air”: Seeking and scanning for information about pre-exposure prophylaxis among young-adult men who have sex with men in the US.. Health Communication, 1-12. https://doi.org/10.1080/10410236.2025.2536314
Long, J., Cunningham, P., Maksi, S., Keller, K., Brick, T., Klippel, A., Boot, L., Cheah, C., Edwards, C., Rolls, B., & Masterson, T. (). Energy Density Selected in Immersive Virtual Reality Buffet Meals Is Associated with Both Energy Density Consumed and Energy Intake in Laboratory Meals. , 27-35. https://doi.org/10.1109/ICVR66534.2025.11172660
Cho, Y., Huang, Y., Chow, S., & Martire, L. (). Couple synchrony in physical activity: Effects on individuals with knee osteoarthritis. Annals of Behavioral Medicine, 59(1). https://doi.org/10.1093/abm/kaaf092
Lee, S., Fisher, Z., & Almeida, D. (). Daily reciprocal relationships between affect, physical activity, and sleep in middle and later life. Annals of Behavioral Medicine, 59(1). https://doi.org/10.1093/abm/kaae072
Knapp, K., Petrie, D., Brick, T., Deneke, E., Bunce, S., & Cleveland, H. (). Within-Person Affect Dynamics Among Individuals in Residential Treatment for Opioid Use Disorder: An Ecological Momentary Assessment Study. Journal of Psychopathology and Clinical Science, 134(2), 184-200. https://doi.org/10.1037/abn0000975
Bhat, Y., Keller, K., Brick, T., & Pearce, A. (). ByteTrack: a deep learning approach for bite count and bite rate detection using meal videos in children. Frontiers in Nutrition, 12, 1610363. https://doi.org/10.3389/fnut.2025.1610363
Long, J., Cunningham, P., Maksi, S., Keller, K., Cheah, C., Boot, L., Klippel, A., Brick, T., Edwards, C., Kort, J., Grabusky, P., Rolls, B., & Masterson, T. (). Variety-seeking behavioral markers in an immersive virtual reality food buffet are associated with greater food and energy intake in laboratory meals. Appetite, 210(1), 107988. https://doi.org/10.1016/j.appet.2025.107988
Chen, M., Hunter, M., & Chow, S. (). Detecting Critical Change in Dynamics Through Outlier Detection with Time-Varying Parameters. British Journal of Statistical Psychology. https://doi.org/10.1111/bmsp.70010
Williams, L., Heshmati, S., Vandekerckhove, J., & Oravecz, Z. (). Current Methodological Approaches for Studying the Association Between Love and Psychological Well-Being in Daily Life. , 1611-1626. https://doi.org/10.1007/978-3-031-94512-0_75
2024
Kim, Y., Fisher, Z., & Pipiras, V. (). Group Integrative Dynamic Factor Models With Application to Multiple Subject Brain Connectivity. Biometrische Zeitschrift, 66(8). https://doi.org/10.1002/bimj.202300370
Lancaster, J., Apsley, H., Brick, T., Ren, W., & Cleveland, III, H. (). The day-level effects of recovery community center attendance on indicators of recovery wellbeing and risk. Journal of Substance Use and Addiction Treatment, 165. https://doi.org/10.1016/j.josat.2024.209459
Fisher, Z., Pipiras, V., & Kim, Y. (). Structured Estimation of Multiple-Subject Time Series. Multivariate Behavioral Research.
Pohlmann, K., Tawil, N., Brick, T., & Kühn, S. (). When houses wear faces: Reverse correlation applied to architectural design. Journal of Environmental Psychology, 98. https://doi.org/10.1016/j.jenvp.2024.102401
Lane, S., Gates, K., Fisher, Z., Arizmendi, C., & Molenaar, P. (). gimme: Group Iterative Multiple Model Estimation (R Package). CRAN.
Kim, Y., Fisher, Z., & Pipiras, V. (). Group Integrative Dynamic Factor Models for Inter- and Intra-individual Brain Networks.. Biometrical Journal.
Olson, A., Shenk, C., Fisher, Z., Heim, C., Noll, J., Shalev, I., & Schreier, H. (). Pre-pandemic individual and household predictors of caregiver and child COVID-19-related stress in a high-risk sample. Child Protection and Practice, 2(2), 9. https://doi.org/10.1016/j.chipro.2024.100046
Hunter, M., Fisher, Z., & Geier, C. (). What ergodicity means for you. Developmental Cognitive Neuroscience, 68. https://doi.org/10.1016/j.dcn.2024.101406