Publications

2019

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., Jenkins, A., Fredman, S., Le, Y., 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, 34(1), 34, 12–23. https://doi.org/10.1037/fam0000573

2018

Yang, F., Zhong, B., Kumar, A., Chow, S., & Ouyang, A. (2018). Exchanging Social Support Online: A Longitudinal Social Network Analysis of Irritable Bowel Syndrome Patients’ Interactions on a Health Forum. Journalism and Mass Communication Quarterly, 95(4), 1033-1057. https://doi.org/10.1177/1077699017729815

Bollen, K., Gates, K., & Fisher, Z. (2018). 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

Santos-Lozada, A., & Howard, J. (2018). Use of death counts from vital statistics to calculate excess deaths in Puerto Rico following Hurricane Maria. JAMA, 320(14), 1491-1493. https://doi.org/10.1001/jama.2018.10929

Wilburne, J., Polly, D., Franz, D., & Wagstaff, D. (2018). 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. (2018). 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

Ji, L., Chow, S., Schermerhorn, A., Jacobson, N., & Cummings, E. (2018). Handling Missing Data in the Modeling of Intensive Longitudinal Data. Structural Equation Modeling, 25(5), 715-736. https://doi.org/10.1080/10705511.2017.1417046

Benson, L., Ram, N., & Stifter, C. (2018). 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

Chow, S., Ou, L., Ciptadi, A., Prince, E., You, D., Hunter, M., Rehg, J., Rozga, A., & Messinger, D. (2018). 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

Anders, R., Oravecz, Z., & Alario, F. (2018). 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

Forgeard, M., & Benson, L. (2018). 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. (2018). 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. (2018). 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. (2018). 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

Lieberman, J., De Souza, M., Wagstaff, D., & Williams, N. (2018). 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. (2018). 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. (2018). 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

Chang, B., Fisher, Z., Bollen, K., Mintz, A., Flotron, S., Borde, A., Swor, R., Peak, D., Rathlev, N., & McLean, S. (2018). Contributions of Minor Traumatic Brain Injury to the Development of Posttraumatic Stress Following Motor Vehicle Accident. Biological Psychiatry, 83(9).

Brinberg, M., Ram, N., Hülür, G., Brick, T., & Gerstorf, D. (2018). Analyzing dyadic data using grid-sequence analysis: Interdyad differences in intradyad dynamics. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 73(1), 5-18. https://doi.org/10.1093/geronb/gbw160

Wood, J., Oravecz, Z., Vogel, N., Benson, L., Chow, S., Cole, P., Conroy, D., Pincus, A., & Ram, N. (2018). Modeling intraindividual dynamics using stochastic differential equations:age differences inaffect regulation. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 73(1), 171-184. https://doi.org/10.1093/geronb/gbx013

Muth, C., Oravecz, Z., & Gabry, J. (2018). User-friendly Bayesian regression modeling: A tutorial with rstanarm and shinystan: Quantitative Methods for Psychology. Quantitative Methods for Psychology, 14(2), 99-119. https://doi.org/10.20982/tqmp.14.2.p099

Oravecz, Z., Wood, J., & Ram, N. (2018). Fitting continuous time stochastic process models in the Bayesian framework.. Continuous Time Modeling in the Behavioral and Related Sciences, 55-78. https://doi.org/10.1007/978-3-319-77219-6_3

Varangis, E., Razlighi, Q., Habeck, C., Fisher, Z., & Stern, Y. (2018). 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

Snoke, J., Brick, T., Slavković, A., & Hunte, M. (2018). 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