2017
Cole, P., Bendezú, J., Ram, N., & Chow, S. (). Dynamical Systems Modeling of Early Childhood Self-Regulation. Emotion, 17(4), 684–699. http://doi.org/10.1037/emo0000268
Oravecz, Z. (). Hierarchical Condorcet Modeling Toolbox. .
2016
Little, T., Roche, K., Chow, S., Schenck, A., & Byam, L. (). National institutes of health pathways to prevention workshop: Advancing research to prevent youth suicide. Annals of Internal Medicine, 165(11), 795-799. https://doi.org/10.7326/M16-1568
Hunter, M. (). As Good as GOLD: Gram–Schmidt Orthogonalization by Another Name. Psychometrika, 81(4), 969-991. https://doi.org/10.1007/s11336-016-9511-3
Kim, B., Chow, S., Bray, B., & Teti, D. (). Trajectories of mothers’ emotional availability: Relations with infant temperament in predicting attachment security. Attachment & Human Development, 19(1), 38-57. http://doi.org/10.1080/14616734.2016.1252780
Grimm, K., Ram, N., & Estabrook, R. (). Growth Modeling: Structural Equation and Multilevel Modeling Approaches. .
Fife, D., Hunter, M., & Mendoza, J. (). Estimating Unattenuated Correlations With Limited Information About Selection Variables: Alternatives to Case IV. Organizational Research Methods, 19(4), 593-615. https://doi.org/10.1177/1094428115625323
Helm, J., Ram, N., Cole, P., & Chow, S. (). Modeling Self-Regulation as a Process Usinga Multiple Time-Scale Multiphase Latent Basis Growth Model. Structural Equation Modeling, 23(5), 635-648. https://doi.org/10.1080/10705511.2016.1178580
Doub, A., Small, M., Levin, A., LeVangie, K., & Brick, T. (). Identifying users of traditional and Internet-based resources for meal ideas: An association rule learning approach. Appetite, 103, 128-136. https://doi.org/10.1016/j.appet.2016.04.006
Chow, S., Bendezú, J., Cole, P., & Ram, N. (). A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation Models with Mixed Effects. Multivariate Behavioral Research, 51(2), 154-184. http://doi.org/10.1080/00273171.2015.1123138
Rodgers, J., Beasley, W., Bard, D., Meredith, K., D. Hunter, M., Johnson, A., Buster, M., Li, C., May, K., Mason Garrison, S., Miller, W., van den Oord, E., & Rowe, D. (). The NLSY Kinship Links: Using the NLSY79 and NLSY-Children Data to Conduct Genetically-Informed and Family-Oriented Research. Behavior Genetics, 46(4), 538-551. https://doi.org/10.1007/s10519-016-9785-3
Neale, M., Hunter, M., Pritikin, J., Zahery, M., Brick, T., Kirkpatrick, R., Estabrook, R., Bates, T., Maes, H., & Boker, S. (). OpenMx 2.0: Extended Structural Equation and Statistical Modeling. Psychometrika, 81(2), 535-549. https://doi.org/10.1007/s11336-014-9435-8
Koffer, R., Ram, N., Conroy, D., Pincus, A., & Almeida, D. (). Stressor diversity: Introduction and empirical integration into the daily stress model. Psychology and Aging, 31(4), 301-320. http://doi.org/10.1037/pag0000095
Lydon-Staley, D., Ram, N., Conroy, D., Pincus, A., Geier, C., & Maggs, J. (). The within-person association between alcohol use and sleep duration and quality in situ: An experience sampling study. Addictive Behaviors, 61, 68-73. http://doi.org/10.1016/j.addbeh.2016.05.018
McDonald, N., Baker, J., & Messinger, D. (). Oxytocin and parent–child interaction in the development of empathy among children at risk for autism. Developmental Psychology, 52(5), 735-745. http://doi.org/10.1037/dev0000104
Oravecz, Z., Muth, C., & Vandekerckhove, J. (). Do people agree on what makes one feel loved? A cognitive psychometric approach to the consensus on felt love. PLoS One, 11(4). https://doi.org/10.1371/journal.pone.0152803
Gangi, D., Messinger, D., Martin, E., & Cuccaro, M. (). Dopaminergic variants in siblings at high risk for autism: Associations with initiating joint attention. Autism Research, 9(11), 1142-1150. http://doi.org/10.1002/aur.1623
Neale, M., Clark, S., Dolan, C., & Hunter, M. (). Regime Switching Modeling of Substance Use: Time-Varying and Second-Order Markov Models and Individual Probability Plots. Structural Equation Modeling, 23(2), 221-233. https://doi.org/10.1080/10705511.2014.979932
Chow, S., Bendezú, J., Cole, P., & Ram, N. (). A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation Models with Mixed Effects. Multivariate Behavioral Research, 51(2), 154-184. https://doi.org/10.1080/00273171.2015.1123138
Chow, S., Lu, Z., Sherwood, A., & Zhu, H. (). Fitting Nonlinear Ordinary Differential Equation Models with Random Effects and Unknown Initial Conditions Using the Stochastic Approximation Expectation–Maximization (SAEM) Algorithm. Psychometrika, 81(1), 102-134. https://doi.org/10.1007/s11336-014-9431-z
Oravecz, Z., Tuerlinckx, F., & Vandekerckhove, J. (). Bayesian Data Analysis with the Bivariate Hierarchical Ornstein-Uhlenbeck Process Model. Multivariate Behavioral Research, 51(1), 106-119. https://doi.org/10.1080/00273171.2015.1110512
Ou, L., Chow, S., Ji, L., & Molenaar, P. (). An Examination of Initial Condition Specification in Autoregressive Latent Trajectory Models. Multivariate Behavioral Research.
Hu, Q., Hu, Q., Bezawada, S., Bezawada, S., Gray, A., Gray, A., Tucker, C., & Brick, T. (). Exploring the link between task complexity and students' affective states during engineering laboratory activities. ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 0, V003T04A019–V003T04A019. https://doi.org/10.1115/DETC2016-59757
Vogel, N., Ram, N., Conroy, D., Pincus, A., & Gerstorf, D. (). How the Social Ecology and Social Situation Shape Individuals’ Affect Valence and Arousal. Emotion, 17(3), 509–527. http://doi.org/10.1037/emo0000244
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