2020
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
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
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
Fisher, Z. (). Robust Estimation and Dynamic Models. .
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
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
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
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
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
McKee, K., Hunter, M., & Neale, M. (). A Method of Correcting Estimation Failure in Latent Differential Equations with Comparisons to Kalman Filtering. Manuscript Under Review. https://doi.org/10.1080/00273171.2019.1642730
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.
Heshmati, S., Oravecz, Z., Pressman, S., Batchelder, W., Muth, C., & Vandekerckhove, J. (). What does it mean to feel loved: Cultural consensus and individual differences in felt love. Journal of Social and Personal Relationships, 36(1), 214-243. https://doi.org/10.1177/0265407517724600
Girault, J., Arizmendi, C., Fisher, Z., Urban, C., Piven, J., & Gates, K. (). Identifying Age-Related Functional Connectivity Features Across Different Levels of Spatial Resolution: An Application of Multi-Scale GIMME: Brain Initiative. .
Li, Y., Ji, L., Oravecz, Z., Hunter, M., & Chow, S. (). dynr.mi: An R Program for Multiple Imputation in Dynamic Modeling. , 305-341. https://doi.org/10.5281/zenodo.3298841
Roberts, N., Oravecz, Z., Sprague, B., & Geier, C. (). A novel hierarchical later process model: Evaluating latent sources of variation in reaction times of adult daily smokers. Frontiers in Psychiatry, 10(0), 474. https://doi.org/10.3389/fpsyt.2019.00474
Lu, Z., Chow, S., Ram, N., & Cole, P. (). Zero-Inflated Regime-Switching Stochastic Differential Equation Models for Highly Unbalanced Multivariate, Multi-Subject Time-Series Data. Psychometrika. https://doi.org/10.1007/s11336-019-09664-7
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. https://doi.org/10.1080/00273171.2019.1697863
Varangis, E., Razlighi, Q., Habeck, C., Fisher, Z., & Stern, Y. (). Between-Network Functional Connectivity is Modified by Age and Cognitive Task Domain. Journal of Cognitive Neuroscience, 31(4), 607--622. https://doi.org/10.1162/jocn_a_01368
Ji, L., Chen, M., Oravecz, Z., Lu, Z., & Chow, S. (). A Bayesian Vector Autoregressive Model with Nonignorable Missingness in Dependent Variables and Covariates: Development, Evaluation, and Application to Family Processes. Structural Equation Modeling, 1-26. https://doi.org/10.1080/10705511.2019.1623681
Li, Y., Ji, L., Oravecz, Z., Hunter, M., & Chow, S. (). dynr.mi: An R Program for Multiple Imputation in Dynamic Modeling: Proceedings of the International Conference on Computational Social Science (ICCSS 2019). , 305-314.
You, D., Hunter, M., Chen, M., & Chow, S. (). A Diagnostic Procedure for Detecting Outliers in Linear State–Space Models. Multivariate Behavioral Research, 231-255. https://doi.org/10.1080/00273171.2019.1627659