2018
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
Ji, L., Chow, S., Schermerhorn, A., Jacobson, N., & Cummings, E. (). 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. (). 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. (). 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
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
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
Gates, K., Fisher, Z., Bollen, K., & Henry, T. (). Identifying and Estimating Relations Within and Between Functional Brain Networks using MIIVsem and GIMME: Modern Modeling Methods. .
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
Surachman, A., Wardecker, B., Chow, S., & Almeida, D. (). Life Course Socioeconomic Status, Daily Stressors, and Daily Well-Being: Examining Chain of Risk Models. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 74, 1(1), 126-135. https://doi.org/10.1093/geronb/gby014
Garrison, S., O'Keefe, P., Hunter, M., Beasley, W., Bard, D., & Rodgers, J. (). AC'RE model: Estimating rearing effects without twins raised apart: Behavior Genetics. , 48(6), 472--472.
Brick, T., Gray, A., & Staples, A. (). Recurrence quantification for the analysis of coupled processes in aging. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 73(1), 134-147. https://doi.org/10.1093/geronb/gbx018
Henry, T., Fisher, Z., & Bollen, K. (). Bayesian model averaging for model implied instrumental variable two stage least squares estimators. arXiv preprint arXiv:1808.10522.
Chang, B., Fisher, Z., Bollen, K., Mintz, A., Flotron, S., Borde, A., Swor, R., Peak, D., Rathlev, N., & McLean, S. (). Contributions of Minor Traumatic Brain Injury to the Development of Posttraumatic Stress Following Motor Vehicle Accident. Biological Psychiatry, 83(9).
Benson, L., Ram, N., Almeida, D., Zautra, A., & Ong, A. (). Fusing Biodiversity Metrics into Investigations of Daily Life: Illustrations and Recommendations With Emodiversity. The Journals of Gerontology: Series B, 73(1), 75–86. http://doi.org/10.1093/geronb/gbx025
Koffer, R., Ram, N., & Almeida, D. (). More than Counting: An Intraindividual Variability Approach to Categorical Repeated Measures. The Journals of Gerontology: Series B, 73(1), 87-99. http://doi.org/10.1093/geronb/gbx086
Brinberg, M., Ram, N., Hülür, G., Brick, T., & Gerstorf, D. (). 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
Brick, T., Koffer, R., Gerstorf, D., & Ram, N. (). Feature selection methods for optimal design of studies for developmental inquiry. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 73(1), 113-123. https://doi.org/10.1093/geronb/gbx008
Chen, M., Chow, S., & Hunter, M. (). Stochastic Differential Equation Models with Time-Varying Parameters. Continuous Time Modeling in the Behavioral and Related Sciences, 205--238. https://doi.org/10.1007/978-3-319-77219-6_9
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
2017
Tang, N., Chow, S., Ibrahim, J., & Zhu, H. (). Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness. Psychometrika, 82(4), 875-903. https://doi.org/10.1007/s11336-017-9587-4
Chow, S., & Hoijtink, H. (). Bayesian Estimation and Modeling: Editorial to the Second Special Issue on Bayesian Data Analysis. Psychological Methods, 22(4), 609-615. https://doi.org/10.1037/met0000169
Morales, S., Ram, N., Buss, K., Cole, P., Helm, J., & Chow, S. (). Age-related changes in the dynamics of fear-related regulation in early childhood. Developmental Science, 21(5), e12633. https://doi.org/10.1111/desc.12633
Szymanski, C., Müller, V., Brick, T., von Oertzen, T., & Lindenberger, U. (). Hyper-transcranial alternating current stimulation: Experimental manipulation of inter-brain synchrony. Frontiers in Human Neuroscience, 11. https://doi.org/10.3389/fnhum.2017.00539