Representative Articles

Please visit my google scholar page for the full list of publications. † Indicates a graduate student under my advisement. 

Gates, K. M.Fisher, Z., Arizmendi, C., Henry, T. R., Duffy, K., & Mucha, P.J. (Accepted). Assessing the Robustness of Cluster Solutions Obtained from Sparse Count Matrices. Psychological Methods. PDF

Bollen, K. A., Gates, K. M., & Fisher, Z. (2018). Robustness conditions for MIIV-2SLS when the latent variable or measurement model is structurally misspecified. Structural Equation Modeling: A Multidisciplinary Journal, 1-12. PDF

Liu, S., Gates, K. M., & Blandon, A. Y. (2018). Directly assessing interpersonal RSA influences in the frequency domain: An illustration with generalized partial directed coherence. Psychophysiology55(6), e13054. PDF

Gates, K. M., Lane, S. T., Varangis, E., Giovanello, K., & Guiskewicz, K. (2017). Unsupervised classification during time-series model building. Multivariate Behavioral Research, 52(2), 129-148. PDF

Lane, S. T. & Gates, K. M. (2017). Automated selection of robust individual-level structural equation models for time series data. Structural Equation Modeling: A Multidisciplinary Journal. 1-15. PDF

Henry, T. & Gates, K. M. (2017). Causal search procedures for fMRI: Review and suggestions. Behaviormetrika, 44(1), 193-225. PDF

Zelle, S. L., Gates, K. M., Fiez, J. A., Sayette, M. A., & Wilson, S. J. (2017). The first day is always the hardest: Functional connectivity during cue exposure and the ability to resist smoking in the initial hours of a quit attempt. NeuroImage, 151, 24-32.

Gates, K.M., Henry, T., Steinley, D. & Fair, D.A. (2016). A Monte Carlo simulation study of weighted community detection algorithms.Frontiers Neuroinformatics, 10. PDF

Gates, K. M. & Liu, S. (2016). Methods for quantifying patterns of dynamic interactions in dyads. Assessment 23(4), 459-471. PDF

Gates, K.M., Gatzke-Kopp, L. M., Sandsten, M., & Blandon, A. Y. (2015). Estimating time-varying RSA to examine psychophysiological linkage in marital dyads. Psychophysiology, 52(8), 1059-1065.PDF

Yang, J., Gates, K. M., Molenaar, P. C. M., & Li, P. (2015). Neural changes underlying successful second language word learning: An fMRI study. Journal of Neurolinguistics, 33, 29-49.

Gates, K.M., Molenaar, P. C. M., Iyer, S. P., Nigg, J. T., & Fair, D. A. (2014). Organizing heterogeneous samples using community detection of GIMME-derived resting state functional networks, PLoS one, 9(3), e91322. PDF

Nichols, T. T., Gates, K. M., Molenaar, P. C. M., & Wilson, S. J. (2013). Greater BOLD activity but more efficient connectivity is associated with better cognitive performance within a sample of nicotine-deprived smokers. Addiction Biology, doi:10.1111/adb.12060. PDF

Beltz, A. M., Gates, K. M., et al. (2013). Changes in alcohol-related brain networks across the first year of college: A prospective pilot study using fMRI connectivity mapping. Addictive Behaviors 38(4), 2052-2059. PDF

Gates, K. M. & Molenaar, P. C. M. (2012). Group search algorithm recovers effective connectivity maps for individuals in homogeneous and heterogeneous samples. NeuroImage 63(1), 310-319. PDF

Gates, K. M., Molenaar, P. C. M., Hillary, F. G., & Slobounov, S. (2011). Extended unified SEM approach for modeling event-related fMRI data. NeuroImage 54(2), 1151-1158. PDF

Gates, K. M., Molenaar, P. C. M., Hillary, F. G., Ram, N., & Rovine, M. J. (2010). Automatic search for fMRI connectivity mapping: an alternative to Granger causality testing using formal equivalences among SEM path modeling, VAR, and unified SEM. NeuroImage 50(3), 1118-1125. PDF