2015
Hammal, Z., Cohn, J., & Messinger, D. (). Head Movement Dynamics during Play and Perturbed Mother-Infant Interaction. IEEE Transactions on Affective Computing, 6(4), 361-370. http://doi.org/10.1109/TAFFC.2015.2422702
Vinciarelli, A., Esposito, A., André, E., Bonin, F., Chetouani, M., Cohn, J., Cristani, M., Fuhrmann, F., Gilmartin, E., Hammal, Z., Heylen, D., Kaiser, R., Koutsombogera, M., Potamianos, A., Renals, S., Riccardi, G., & Salah, A. (). Open Challenges in Modelling, Analysis and Synthesis of Human Behaviour in Human–Human and Human–Machine Interactions. Cognitive Computation, 7(4), 397-413. http://doi.org/10.1007/s12559-015-9326-z
Ebner-Priemer, U., Houben, M., Santangelo, P., Kleindienst, N., Tuerlinckx, F., Oravecz, Z., Verleysen, G., Van Deun, K., Bohus, M., & Kuppens, P. (). Unraveling affective dysregulation in borderline personality disorder: A theoretical model and empirical evidence. Journal of Abnormal Psychology, 124(1), 186-198. https://doi.org/10.1037/abn0000021
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
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
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
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
Fisher, Z., & Tipton, E. (). robumeta: An R-package for Robust Variance Estimation in Meta-analysis. arXiv preprint arXiv:1503.02220.
Oravecz, Z., Faust, K., Batchelder, W., & Levitis, D. (). Studying the existence and attributes of consensus on psychological concepts by a cognitive psychometric model. American Journal of Psychology, 128(1), 61-75. https://doi.org/10.5406/amerjpsyc.128.1.0061
Van der Ark, A., Bolt, D., Wang, W., Douglas, J., & Chow, S. (). Quantitative Psychology Research. .
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. .
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
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
Anders, R., Oravecz, Z., & Batchelder, W. (). Cultural consensus theory for continuous responses: A latent appraisal model for information pooling. Journal of Mathematical Psychology, 61, 1-13. https://doi.org/10.1016/j.jmp.2014.06.001
Oravecz, Z., Vandekerckhove, J., & Batchelder, W. (). Bayesian Cultural Consensus Theory. Field Methods, 26(3), 207-222. https://doi.org/10.1177/1525822X13520280
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
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
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.
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
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.
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). .
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.