2020
Husmann, K., Brick, T., & Estabrook, R. (). mxmmod: Measurement Model of Derivatives in OpenMx. .
Dunton, G., Wang, S., Ponnada, A., Campo, R., Chow, S., & Intille, S. (). INNOVATIVE ECOLOGICAL MOMENTARY ASSESSMENT STRATEGIES TO CAPTURE MICRO-TEMPORAL PROCESSES UNDERLYING LONG-TERM CHANGES IN PHYSICAL ACTIVITY, SEDENTARY BEHAVIOR, AND SLEEP. ANNALS OF BEHAVIORAL MEDICINE, 54, S146-S146.
Shewark, E., Shewark, E., Brick, T., & Buss, K. (). Capturing temporal dynamics of fear behaviors on a moment-to-moment basis. Infancy, 25(3), 264-285. https://doi.org/10.1111/infa.12328
Mundie, J., Weaver, J., Oravecz, Z., & Brick, T. (). Wear-IT Smartphone App and Framework. .
Leonard, K., Evans, B., Evans, M., Oravecz, Z., Smyth, J., & Downs, D. (). Effect of Technology-Supported Interventions on Prenatal Gestational Weight Gain, Physical Activity, and Healthy Eating Behaviors: a Systematic Review and Meta-analysis. Journal of Technology in Behavioral Science, 6(1), 25-41. https://doi.org/10.1007/s41347-020-00155-6
You, D., Hunter, M., Chen, M., & Chow, S. (). A Diagnostic Procedure for Detecting Outliers in Linear State-Space Models. MULTIVARIATE BEHAVIORAL RESEARCH, 55(2), 231-255. https://doi.org/10.1080/00273171.2019.1627659
Heshmati, S., Heshmati, S., Oravecz, Z., Brick, T., & Roeser, R. (). Assessing psychological well-being in early adulthood: Empirical evidence for the structure of daily well-being via network analysis. Applied Developmental Science, 26(2), 207-225. https://doi.org/10.1080/10888691.2020.1766356
Chow, S., You, D., & Clouthier, T. (). A regime-switching framework for formulating multi-phase linear and nonlinear growth curves: MARCES Series: Applications of Artificial Intelligence to Assessment. , 193-234.
Ji, L., Chow, S., Crosby, B., & Teti, D. (). Exploring Sleep Dynamic of Mother-Infant Dyads Using a Regime-Switching Vector Autoregressive Model.. Multivariate Behavioral Research, 55(1), 150-151. https://doi.org/10.1080/00273171.2019.1697863
Bastiaansen, J., Kunkels, Y., Blaauw, F., Boker, S., Ceulemans, E., Chen, M., Cheng, M., Chow, S., Jonge, P., de Jonge, Peter, , de Jonge, P., Emerencia, A., Epskamp, S., Fisher, A., Hamaker, E., Kuppens, P., Lutz, W., Meyer, M., Moulder, R., Oravecz, Z., et al (). Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology. Journal of Psychosomatic Research, 137, 110211. https://doi.org/10.1016/j.jpsychores.2020.110211
Fisher, Z. (). Robust Estimation and Dynamic Models. .
Knapp, K., Brick, T., Bunce, S., Bunce, S., Brick, T., Deneke, E., & Cleveland, H. (). Daily associations among craving, affect, and social interactions in the lives of patients during residential opioid use disorder treatment.. Psychology of Addictive Behaviors. https://doi.org/10.1037/adb0000612
Osotsi, A., Osotsi, A., Oravecz, Z., Li, Q., Smyth, J., & Brick, T. (). Individualized Modeling to Distinguish Between High and Low Arousal States Using Physiological Data. Journal of Healthcare Informatics Research, 4(1), 91--109. https://doi.org/10.1007/s41666-019-00064-1
Cole, P., Lougheed, J., Chow, S., & Ram, N. (). Development of Emotion Regulation Dynamics Across Early Childhood: a Multiple Time-Scale Approach. Affective Science, 1(1), 28-41. https://doi.org/10.1007/s42761-020-00004-y
Chow, S., & Chen, M. (). Nonparametric models for longitudinal data: With implementation in R. JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS, 45(3), 369-373. https://doi.org/10.3102/1076998620915291
2019
Gates, K., Fisher, Z., Arizmendi, C., Henry, T., Duffy, K., & Mucha, P. (). Assessing the robustness of cluster solutions obtained from sparse count matrices. Psychological Methods, 24(6), 675-689. https://doi.org/10.1037/met0000204
Adams, E., Marini, M., Brick, T., Paul, I., Birch, L., & Savage, J. (). Ecological momentary assessment of using food to soothe during infancy in the INSIGHT trial. International Journal of Behavioral Nutrition and Physical Activity, 16(1). https://doi.org/10.1186/s12966-019-0837-y
Chow, S. (). Practical Tools and Guidelines for Exploring and Fitting Linear and Nonlinear Dynamical Systems Models. Multivariate Behavioral Research, 54(5), 690-718. https://doi.org/10.1080/00273171.2019.1566050
Rodgers, J., Garrison, S., O’Keefe, P., Bard, D., Hunter, M., Beasley, W., & van den Oord, E. (). Responding to a 100-Year-Old Challenge from Fisher: A Biometrical Analysis of Adult Height in the NLSY Data Using Only Cousin Pairs. Behavior Genetics, 49(5), 444-454. https://doi.org/10.1007/s10519-019-09967-6
Oravecz, Z., & Brick, T. (). Associations Between Slow- and Fast-Timescale Indicators of Emotional Functioning. Social Psychological and Personality Science, 10(7), 864-873. https://doi.org/10.1177/1948550618797128
Dopp, A., Mundey, P., Silovsky, J., Hunter, M., & Slemaker, A. (). Economic value of community-based services for problematic sexual behaviors in youth: A mixed-method cost-effectiveness analysis. Child Abuse & Neglect, 105, 1-11. https://doi.org/10.1016/j.chiabu.2019.104043
Ou, L., Hunter, M., & Chow, S. (). What's for dynr: A package for linear and nonlinear dynamic modeling in R. R Journal, 11(1). https://doi.org/10.32614/rj-2019-012
Fisher, Z., Bollen, K., & Gates, K. (). A Limited Information Estimator for Dynamic Factor Models. Multivariate Behavioral Research, 54(2), 246-263. https://doi.org/10.1080/00273171.2018.1519406
Silovsky, J., Hunter, M., & Taylor, E. (). Impact of early intervention for youth with problematic sexual behaviors and their caregivers. Journal of Sexual Aggression, 25(1), 4-15. https://doi.org/10.1080/13552600.2018.1507487
Li, Y., Ji, L., Oravecz, Z., Brick, T., Hunter, M., & Chow, S. (). dynr.mi: An R Program for Multiple Imputation in Dynamic Modeling: eISSN:1307-6892. World Academy of Science, Engineering and Technology, International Science Index 149, 2019. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 13(5), 302-311.