2025
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
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
Oh, H., Hunter, M., & Chow, S. (). Measurement Model Misspecification in Dynamic Structural Equation Models: Power, Reliability, and Other Considerations. Structural Equation Modeling, 32(3), 511--528. https://doi.org/10.1080/10705511.2025.2452884
Alexander, J., Duffy, K., Freis, S., Chow, S., Friedman, N., & Vrieze, S. (). Investigating the Magnitude and Persistence of COVID-19–Related Impacts on Affect and GPS-Derived Daily Mobility Patterns in Adolescence and Emerging Adulthood: Insights From a Smartphone-Based Intensive Longitudinal Study of Colorado-Based Youths From…. Journal of Medical Internet Research, 27, e64965. https://doi.org/10.2196/64965
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
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.
Hunter, M., Fisher, Z., & Geier, C. (). What ergodicity means for you. Developmental Cognitive Neuroscience, 68. https://doi.org/10.1016/j.dcn.2024.101406
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
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
Park, J., Chow, S., & Molenaar, P. (). What the fuzz: Dependent Data in Social Sciences Research. Springer Proceedings in Mathematics & Statistics. , 2, 161-180.
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
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
Chow, S., Lee, J., Park, J., Chow, S., Kuruppumullage Don, P., Kuruppumallage Don, P., Hammel, T., Hallquist, M., Nord, E., Oravecz, Z., Perry, H., Lesser, L., Ram, N., Pearl, D., Lesser, L., others, , & Pearl, D. (). Personalized Education through Individualized Pathways and Resources to Adaptive Control Theory-Inspired Scientific Education (iPRACTISE): Proof-of-Concept Studies for Designing and Evaluating Personalized Education. Journal of Statistics and Data Science Education, 32(2), 174-187. https://doi.org/10.1080/26939169.2024.2302181
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
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
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.