2020
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
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
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
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
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
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
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
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. .
Schneider, J., & Brick, T. (). plsR: Partial Least Squares Analysis for Dummies. .
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
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.
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
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
Knapp, K., Cleveland, H., Brick, T., & Bunce, S. (). 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
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
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.
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
Kolanowski, A., Behrens, L., Lehman, E., Oravecz, Z., Oravecz, Z., Resnick, B., Resnick, B., Lehman, E., Boltz, M., Van Haitsma, K., Galik, E., Ellis, J., & Eshraghi, K. (). Living well with dementia: Factors associated with nursing home residents’ affect balance. Research in gerontological nursing, 13(1), 21-30. https://doi.org/10.3928/19404921-20190823-01