2026
Albers, C., & Hunter, M. (). Editorial: Special Issue on Multiple multivariate multimodal time series data analysis in psychological research. British Journal of Statistical Psychology, 79(2), 233-236. https://doi.org/10.1111/bmsp.70046
Whitney, J., Suhy, V., Pauley, A., Shao, D., Khan, O., Moore, A., Chow, S., Rivera, D., & Downs, D. (). Game, Set, and Match: A Scoping Review of Matching Characteristics for Control and Intervention Groups in Adaptive Behavioral Interventions for Physical Activity or Healthy Eating Designs for Populations with Overweight and Obesity. Journal of Human Stress. https://doi.org/10.1080/08964289.2026.2641440
Hunter, M. (). Extending reliability to intensive longitudinal data with the Kalman filter. British Journal of Statistical Psychology. https://doi.org/10.1111/bmsp.70039
Hunter, M., Garrison, S., Lyu, X., Good, R., Carroll, S., & Burt, S. (). Tracing the Right Path: Determination of Large Pedigree Segmentation and Relatedness. Behavior Genetics. https://doi.org/10.1007/s10519-026-10259-z
2025
Singh, M., Hunter, M., Assary, E., Verhulst, B., Peterson, R., Maes, H., Dolan, C., Eley, T., & Neale, M. (). Causation Between Smoking Quantity and Depressive Symptoms in Young Adults: Evidence From Novel Cross-Lagged Twin Models. medArXiv, 1-40. https://doi.org/10.1101/2025.11.18.25340516
Coles, N., Perz, B., Behnke, M., Eichstaedt, J., Kim, S., Vu, T., Raman, C., Tejada, J., Huynh, V., Zhang, G., Cui, T., Podder, S., Chavda, R., Pandey, S., Upadhyay, A., Padilla-Buritica, J., Barrera Causil, C., Ji, L., Dollack, F., Kiyokawa, K., et al (). Big team science reveals promises and limitations of machine learning efforts to model physiological markers of affective experience. Royal Society Open Science, 12(6). https://doi.org/10.1098/rsos.241778
Heshmati, S., Muth, C., Li, Y., Roeser, R., Smyth, J., Vandekerckhove, J., Chow, S., & Oravecz, Z. (). Who benefits from mobile health interventions? A dynamical systems analysis of psychological well-being in early adults. Applied Psychology: Health and Well-Being, 17(3). https://doi.org/10.1111/aphw.70037
Rosinger, A., McGrosky, A., Jacobson, H., Hinz, E., Sadhir, S., Wambua, F., Otube, T., Baker, L., Sherwood, A., Chrissy-Mbeng, T., Broyles, L., Musumeci, C., Meriwether, N., Bobbie, N., Farrar, Z., Todd, M., Nguyen, Z., Berger, G., Ford, L., Braun, D., et al (). Drinking Water NaCl Is Associated With Hypertension and Albuminuria: A Panel Study. Hypertension, 82(8), 1368-1378. https://doi.org/10.1161/HYPERTENSIONAHA.125.24751
Liu, C., Chow, S., Aris, I., Dabelea, D., Neiderhiser, J., Leve, L., Blair, C., Catellier, D., Couzens, L., Braun, J., Ferrara, A., Aschner, J., Deoni, S., Dunlop, A., Gern, J., Rivera-Spoljaric, K., Hartert, T., Hershey, G., Karagas, M., Kennedy, E., et al (). Early-Life Factors and Body Mass Index Trajectories Among Children in the ECHO Cohort. JAMA network open, 8(5), e2511835. https://doi.org/10.1001/jamanetworkopen.2025.11835
Hunter, M., Kirkpatrick, R., & Neale, M. (). Show Me Some ID: A Universal Identification Program for Structural Equation Models. Psychometrika, 90(2), 418-441. https://doi.org/10.1017/psy.2025.19
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
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
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
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
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
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
Burt, S., Garrison, S., Lyu, X., Rodgers, J., Carroll, S., Smith, K., & Hunter, M. (). Contributions of inherited mtDNA to longevity: evidence from extended pedigrees with 176 million kinship pairs. EBioMedicine, 119(105911), 1-10. https://doi.org/10.1016/j.ebiom.2025.105911
Xiong, X., Hunter, M., & Chow, S. (). Integrated Trend and Lagged Modeling of Multi-Subject, Multilevel, and Short Time Series. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2025.2587286
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
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
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
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
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. JAMA Pediatrics. https://doi.org/10.1001/jamapediatrics.2024.6824
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