Publications

2020

Fisher, Z., Chow, S., Molenaar, P., Molenaar, Peter C. M., , Fredrickson, B., Pipiras, V., & Gates, K. (2020). A Square-Root Second-Order Extended Kalman Filtering Approach for Estimating Smoothly Time-Varying Parameters. Multivariate Behavioral Research, 57(1), 134-152. https://doi.org/10.1080/00273171.2020.1815513

Shewark, E., Shewark, E., Brick, T., & Buss, K. (2020). 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. (2020). Wear-IT Smartphone App and Framework. .

Leonard, K., Evans, B., Evans, M., Oravecz, Z., Smyth, J., & Downs, D. (2020). 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

Fisher, Z. (2020). Robust Estimation and Dynamic Models. .

Husmann, K., Brick, T., & Estabrook, R. (2020). mxmmod: Measurement Model of Derivatives in OpenMx. .

Osotsi, A., Osotsi, A., Oravecz, Z., Li, Q., Smyth, J., & Brick, T. (2020). 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

Heshmati, S., Heshmati, S., Oravecz, Z., Brick, T., & Roeser, R. (2020). 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

2019

Gates, K., Fisher, Z., Arizmendi, C., Henry, T., Duffy, K., & Mucha, P. (2019). 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. (2019). 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

Rodgers, J., Garrison, S., O’Keefe, P., Bard, D., Hunter, M., Beasley, W., & van den Oord, E. (2019). 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. (2019). 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. (2019). 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. (2019). 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. (2019). 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. (2019). 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

Girault, J., Arizmendi, C., Fisher, Z., Urban, C., Piven, J., & Gates, K. (2019). Identifying Age-Related Functional Connectivity Features Across Different Levels of Spatial Resolution: An Application of Multi-Scale GIMME: Brain Initiative. .

Knapp, K., Cleveland, H., Brick, T., & Bunce, S. (2019). Exploring daily processes of addiction: Associations between social experiences and craving among opioid addicts in treatment: Annals of Behavioral Medicine. , 53, S398--S398. https://doi.org/10.1115/DETC2016-59757

Li, Y., Ji, L., Oravecz, Z., Hunter, M., & Chow, S. (2019). 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. (2019). 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

Varangis, E., Razlighi, Q., Habeck, C., Fisher, Z., & Stern, Y. (2019). 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

Hepworth, A., Brick, T., & Small, M. (2019). Exploring Parents’ Satisfaction with Infant and Toddler Feeding Information: A Repeated-Measures Analysis of Information Need and Acquisition Characteristics (P17-006-19). Current developments in nutrition, 3(0), nzz038--P17. https://doi.org/10.1093/cdn/nzz038.P17-006-19

Jenkins, A., Fredman, S., Le, Y., Sun, X., Brick, T., Skinner, O., & McHale, S. (2019). Prospective associations between depressive symptoms and marital satisfaction in Black couples. Journal of Family Psychology. https://doi.org/10.1037/fam0000573

Ji, L., Chen, M., Oravecz, Z., Lu, Z., & Chow, S. (2019). 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. (2019). dynr.mi: An R Program for Multiple Imputation in Dynamic Modeling: Proceedings of the International Conference on Computational Social Science (ICCSS 2019). , 305-314.