2016
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
Ram, N., Benson, L., Brick, T., Conroy, D., & Pincus, A. (). Behavioral Landscapes and Earth Mover’s Distance: A New Approach for Studying Individual Differences in Density Distributions. Journal of Research in Personality, 69, 191-205. https://doi.org/10.1016/j.jrp.2016.06.010
Snoke, J., Brick, T., & Slavković, A. (). Accurate estimation of structural equation models with remote partitioned data. , 190-209. https://doi.org/10.1007/978-3-319-45381-1_15
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.
Snoke, J., Brick, T., & Slavkovic, A. (). Accurate Estimation of Structural Equation Models with Remote Partitioned Data: Privacy in Statistical Databases: UNESCO Chair in Data Privacy, International Conference (PSD 2016). , 190--209. https://doi.org/10.1007/978-3-319-45381-1_15
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
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
Lu, Z., Chow, S., Sherwood, A., & Zhu, H. (). Bayesian analysis of ambulatory blood pressure dynamics with application to irregularly spaced sparse data. Annals of Applied Statistics, 9(3), 1601-1620. https://doi.org/10.1214/15-AOAS846
Maher, J., Pincus, A., Ram, N., & Conroy, D. (). Daily physical activity and life satisfaction across adulthood. Developmental Psychology, 51(10), 1407-1419. http://doi.org/10.1037/dev0000037
Van Der Ark, L., Bolt, D., Wang, W., Douglas, J., & Chow, S. (). Quantitative Psychology Research: The 79th Annual Meeting of the Psychometric Society, Madison, Wisconsin, 2014. , 140. https://doi.org/10.1007/978-3-319-19977-1
Oravecz, Z., Anders, R., & Batchelder, W. (). Hierarchical Bayesian Modeling for Test Theory Without an Answer Key. Psychometrika, 80(2), 341-364. https://doi.org/10.1007/s11336-013-9379-4
Pritikin, J., Hunter, M., & Boker, S. (). Modular Open-Source Software for Item Factor Analysis. Educational and Psychological Measurement, 75(3), 458-474. https://doi.org/10.1177/0013164414554615
Ozonoff, S., Young, G., Landa, R., Brian, J., Bryson, S., Charman, T., Chawarska, K., Macari, S., Messinger, D., Stone, W., Zwaigenbaum, L., & Iosif, A. (). Diagnostic stability in young children at risk for autism spectrum disorder: A baby siblings research consortium study. Journal of Child Psychology and Psychiatry, 56(9), 988-998. http://doi.org/10.1111/jcpp.12421