2017
Fisher, Z., Bollen, K., Gates, K., & R\"onkk\"o, M, (). MIIVsem: An R Package for Instrumental Variable Estimation of Structural Equation Models. R package version 0.5, 2.
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
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. .
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
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
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
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
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. .
Ou, L., Chow, S., Ji, L., & Molenaar, P. (). An Examination of Initial Condition Specification in Autoregressive Latent Trajectory Models. Multivariate Behavioral Research.
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
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
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
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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