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
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., 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
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
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
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
Fisher, Z., Bollen, K., Lindquist, K., Doyle, C., & Gates, K. (). Unified Estimation of Between- and Within-Network Relationships in High-Dimensional fMRI Time Series.: Organization for Human Brain Mapping. .
Oravecz, Z., Huentelman, M., & Vandekerckhove, J. (). Sequential bayesian updating for big data. , 13-33. https://doi.org/10.4324/9781315413570
Ou, L., Chow, S., Ji, L., & Molenaar, P. (). An Examination of Initial Condition Specification in Autoregressive Latent Trajectory Models. Multivariate Behavioral Research.
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2015
Aviezer, H., Messinger, D., Zangvil, S., Mattson, W., Gangi, D., & Todorov, A. (). Thrill of victory or agony of defeat?: Perceivers fail to utilize information in facial movements. Emotion, 15(6), 791-797. http://doi.org/10.1037/emo0000073
Ruvolo, P., Messinger, D., & Movellan, J. (). Infants Time Their Smiles to Make Their Moms Smile. PLOS ONE, 10(9). http://doi.org/10.1371/journal.pone.0136492