Publications

2019

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.
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
Schneider, J., & Brick, T. (). plsR: Partial Least Squares Analysis for Dummies. .
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
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.
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
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. .
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
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

2018

Bollen, K., Gates, K., & Fisher, Z. (). Robustness Conditions for MIIV-2SLS When the Latent Variable or Measurement Model is Structurally Misspecified. Structural Equation Modeling, 25(6), 848-859. https://doi.org/10.1080/10705511.2018.1456341
Wilburne, J., Polly, D., Franz, D., & Wagstaff, D. (). Mathematics teachers' implementation of high-leverage teaching practices: A Q-sort study. School Science and Mathematics, 118(6), 232-243. https://doi.org/10.1111/ssm.12293
Graham-Engeland, J., Song, S., Mathur, A., Wagstaff, D., Klein, L., Whetzel, C., & Ayoub, W. (). Emotional State Can Affect Inflammatory Responses to Pain Among Rheumatoid Arthritis Patients: Preliminary Findings. Psychological Reports, 122(6), 2026-2049. https://doi.org/10.1177/0033294118796655
Benson, L., Ram, N., & Stifter, C. (). Using Fishery Models to Examine Self- and Co-Regulation Processes Across Multiple Timescales. Structural Equation Modeling: A Multidisciplinary Journal, 25(6), 906-923. http://doi.org/10.1080/10705511.2018.1491313
Anders, R., Oravecz, Z., & Alario, F. (). Improved information pooling for hierarchical cognitive models through multiple and covaried regression. Behavior Research Methods, 50(3), 989-1010. https://doi.org/10.3758/s13428-017-0921-7
Chow, S., Ou, L., Ciptadi, A., Prince, E., You, D., Hunter, M., Rehg, J., Rozga, A., & Messinger, D. (). Representing Sudden Shifts in Intensive Dyadic Interaction Data Using Differential Equation Models with Regime Switching. Psychometrika, 83(2), 476-510. https://doi.org/10.1007/s11336-018-9605-1
Forgeard, M., & Benson, L. (). Extracurricular involvement and psychological adjustment in the transition from adolescence to emerging adulthood: The role of mastery and creative self-efficacy. Applied Developmental Science, 201, 1-18. http://doi.org/10.1080/10888691.2017.1288124
Pritikin, J., Brick, T., & Neale, M. (). Multivariate normal maximum likelihood with both ordinal and continuous variables, and data missing at random. Behavior Research Methods, 50(2), 490-500. https://doi.org/10.3758/s13428-017-1011-6
Baribault, B., Donkin, C., Little, D., Trueblood, J., Oravecz, Z., Van Ravenzwaaij, D., White, C., De Boeck, P., & Vandekerckhove, J. (). Metastudies for robust tests of theory. Proceedings of the National Academy of Sciences of the United States of America, 115(11), 2607-2612. https://doi.org/10.1073/pnas.1708285114
Hunter, M. (). State Space Modeling in an Open Source, Modular, Structural Equation Modeling Environment. Structural Equation Modeling, 25(2), 307-324. https://doi.org/10.1080/10705511.2017.1369354
Batchelder, W., Anders, R., & Oravecz, Z. (). Cultural Consensus Theory: The Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Volume V: Methodology. , 221-264. https://doi.org/10.1002/9781119170174.epcn506
Lieberman, J., De Souza, M., Wagstaff, D., & Williams, N. (). Menstrual Disruption with Exercise Is Not Linked to an Energy Availability Threshold. Medicine & Science in Sports & Exercise, 50(3), 551-561. http://doi.org/10.1249/MSS.0000000000001451
Oravecz, Z., & Muth, C. (). Fitting growth curve models in the Bayesian framework. Psychonomic Bulletin and Review, 25(1), 235-255. https://doi.org/10.3758/s13423-017-1281-0
Helm, J., Castro-Schilo, L., Zavala-Rojas, D., DeCastellarnau, A., & Oravecz, Z. (). Bayesian Estimation of the True Score Multitrait–Multimethod Model With a Split-Ballot Design. Structural Equation Modeling, 25(1), 71-85. https://doi.org/10.1080/10705511.2017.1378103
Snoke, J., Brick, T., Slavković, A., & Hunte, M. (). Providing accurate models across private partitioned data: Secure maximum likelihood estimation. Annals of Applied Statistics, 12(2), 877-914. https://doi.org/10.1214/18-AOAS1171