2025
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
Ringwald, W., Creswell, K., Low, C., Doryab, A., Chung, T., Oliva, J., Fisher, Z., Gates, K., & Wright, A. (). Common and Uncommon Risky Drinking Patterns in Young Adulthood Uncovered by Person-Specific Computational Modeling. Psychology of Addictive Behaviors. https://doi.org/10.1037/adb0001055
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
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
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
Cho, Y., Chow, S., Li, J., Wang, S., Wang, W., Ji, L., Chinchilli, V., Intille, S. S.,, , & Dunton, G. (). Within- and Between-Individual Compliance in Mobile Health: Joint Modeling Approach to Nonrandom Missingness in an Intensive Longitudinal Observational Study. JMIR mHealth and uHealth, 13, e65350. https://doi.org/10.2196/65350
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
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
Fisher, Z., Pipiras, V., & Kim, Y. (). Structured Estimation of Multiple-Subject Time Series. Multivariate Behavioral Research.
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
Ahn, Y., Martin, K., Prince, E., Chow, S., Cohn, J., Wang, J., Simpson, E., & Messinger, D. (). How still? Parent–infant interaction during the still-face and later infant attachment. Infant and Child Development, 33(4). https://doi.org/10.1002/icd.2492
Petrie, D., Meeks, K., Fisher, Z., & Geier, C. (). Associations between somatomotor-putamen resting state connectivity and obsessive-compulsive symptoms vary as a function of stress during early adolescence: Data from the ABCD study. Brain Research Bulletin, 210. https://doi.org/10.1016/j.brainresbull.2024.110934
Elavsky, S., Burda, M., Cipryan, L., Kutáč, P., Bužga, M., Jandačková, V., Chow, S., & Jandačka, D. (). Physical activity and menopausal symptoms: evaluating the contribution of obesity, fitness, and ambient air pollution status. Menopause, 31(4), 310-319. https://doi.org/10.1097/GME.0000000000002319
Knapova, L., Cho, Y., Chow, S., Kuhnova, J., & Elavsky, S. (). From intention to behavior: Within- and between-person moderators of the relationship between intention and physical activity. Psychology of Sport and Exercise, 71. https://doi.org/10.1016/j.psychsport.2023.102566
Santos-Lozada, A., & Rivera-Reyes, B. (). Hurricane Fiona and Puerto Rico: Compounding Disasters Complicate PostDisaster Assessments. American Journal of Epidemiology, 193(2), 404-406. https://doi.org/10.1093/aje/kwad204
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
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.
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
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
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