2015
Filevich, E., Dresler, M., Brick, T., & Kühn, S. (). Metacognitive mechanisms underlying lucid dreaming. Journal of Neuroscience, 35(3), 1082-1088. https://doi.org/10.1523/JNEUROSCI.3342-14.2015
Conroy, D., Ram, N., Pincus, A., Coffman, D., Lorek, A., Rebar, A., & Roche, M. (). Daily physical activity and alcohol use across the adult lifespan. Health Psychology, 34(6), 653-660. http://doi.org/10.1037/hea0000157
Van Der Ark, L., Bolt, D., Wang, W., Douglas, J., & Chow, S. (). Preface. Springer Proceedings in Mathematics and Statistics, 140, V. https://doi.org/10.1007/978-3-319-19977-1
Van der Ark, A., Bolt, D., Wang, W., Douglas, J., & Chow, S. (). Quantitative Psychology Research. .
Fisher, Z., & Tipton, E. (). robumeta: An R-package for Robust Variance Estimation in Meta-analysis. arXiv preprint arXiv:1503.02220.
Boker, S., Brick, T., Pritikin, J., Wang, Y., von Oertzen, T., Brown, D., Lach, J., Estabrook, R., Hunter, M., Maes, H., & Neale, M. (). Maintained individual data distributed likelihood estimation (MIDDLE). Multivariate Behavioral Research, 50(6), 706-720. https://doi.org/10.1080/00273171.2015.1094387
Loken, E., Oravecz, Z., Tucker, C., & Linder, F. (). Psychometric analysis of residence and MOOC assessments. ASEE Annual Conference and Exposition, Conference Proceedings, 122(122). https://doi.org/10.18260/p.24621
Mårtensson, J., Eriksson, J., Brick, T., Lindgren, M., Johansson, M., Nyberg, L., & Lovdén, M. (). Proficiency and brain structure during intense language learning: Microstructures of Learning Novel methods and approaches for assessing structural and functional changes underlying knowledge acquisition in the brain. .
Koffer, R., Koffer, R., Ram, N., Brick, T., Almeida, D., & Tucker, C. (). MACHINE LEARNING AND GERONTOLOGY: BOOSTED REGRESSION TREES PREDICT AGE DIFFERENCES IN STRESSOR EXPERIENCE: GERONTOLOGIST. , 55(0), 461--462. https://doi.org/10.1093/geront/gnv195.10
2014
Kühn, S., Brick, T., Müller, B., & Gallinat, J. (). Is this car looking at you? How anthropomorphism predicts fusiform face area activation when seeing cars. PLoS One, 9(12), e113885. https://doi.org/10.1371/journal.pone.0113885
Conroy, D., Ram, N., Pincus, A., & Rebar, A. (). Bursts of Self-Conscious Emotions in the Daily Lives of Emerging Adults. Self and Identity, 14(3), 290-313. http://doi.org/10.1080/15298868.2014.983963
Zhang, G., Browne, M., Ong, A., & Chow, S. (). Analytic Standard Errors for Exploratory Process Factor Analysis. Psychometrika, 79(3), 444-469. https://doi.org/10.1007/s11336-013-9365-x
Messinger, D., Duvivier, L., Warren, Z., Mahoor, M., Baker, J., Warlaumont, A., & Ruvolo, P. (). The Oxford Handbook of Affective Computing: Affective Computing, Emotional Development, and Autism. . http://doi.org/10.1093/oxfordhb/9780199942237.013.012
von Oertzen, T., & Brick, T. (). Efficient Hessian computation using sparse matrix derivatives in RAM notation. Behavior Research Methods, 46(2), 385-395. https://doi.org/10.3758/s13428-013-0384-4
Ram, N., Conroy, D., Pincus, A., Lorek, A., Rebar, A., Roche, M., Coccia, M., Morack, J., Feldman, J., & Gerstorf, D. (). Examining the Interplay of Processes Across Multiple Time-Scales: Illustration With the Intraindividual Study of Affect, Health, and Interpersonal Behavior (iSAHIB). Research in Human Development, 11(2), 142-160. http://doi.org/10.1080/15427609.2014.906739
Hutton, R., & Chow, S. (). Longitudinal Multi-Trait-State-Method Model Using Ordinal Data. Multivariate Behavioral Research, 49(3), 269-282. https://doi.org/10.1080/00273171.2014.903832
Hunter, M. (). Abstract: Dynamic Mixture Modeling of a Single Simulated Case. Multivariate Behavioral Research, 49(3), 286--287. https://doi.org/10.1080/00273171.2014.912890
Messinger, D., Mahoor, M., Chow, S., Haltigan, J., Cadavid, S., & Cohn, J. (). Early Emotional Communication: Novel Approaches to Interaction. . https://doi.org/10.1093/acprof:oso/9780195387643.003.0011
Ledoux, K., Fisher, Z., Kuo, S., & Gordon, B. (). Using Mismatch Negativity to Study Speech Perception in a Low-Functioning Individual with Autism: Annals of Neurology. , 76, S24--S24.
Chow, S., Witkiewitz, K., Grassman, R., Hutton, R., & Maisto, S. (). A regime-switihing longitudinal model of alcohol lapse--relapse: Handbook of developmental systems theory and methodology. , 397-422.
Sung, K., Bosley, L., Fisher, Z., & Gordon, B. (). Abnormal Visual ERPs and alpha Band Power in Low-and High-Functioning Individuals with Autism: Annals of Neurology. , 76, 73--74.
Neale, M., Zahery, M., Brick, T., Kirkpatrick, R., Bates, T., Maes, H., Boker, S., Hunter, M., & Pritikin, J. (). OpenMx 2.0: Extended Structural Equation and Statistical Modeling. Psychometrika, 81, 535-549. https://doi.org/10.1007/s11336-014-9435-8
Chow, S., Mattson, W., & Messinger, D. (). Representing trends and moment-to-moment variability in dyadic and family processes using state-space modeling techniques: Emerging Methods in Family Research, National Symposium on Family Issues. , 4, 39-54. https://doi.org/10.1007/978-3-319-01562-0_3
Coderre, E., Fisher, Z., Gordon, B., & Ledoux, K. (). Electrophysiological Measurements of Letter-Sound Correspondence in a Low-Functioning Individual with Autism: Annals of Neurology. , 76, 22--23.
Neale, M., Zahery, M., Brick, T., Kirkpatrick, R., Estabrook, R., Bates, T., Maes, H., Boker, S., Hunter, M., & Pritikin, J. (). OpenMx: Extended Structural Equation Modeling Framework (Latest Version 2.0). .