Kathleen Gates

Katie Gates
Nationality	American
Alma mater	Michigan State University City University of New York Pennsylvania State University
Known for	Group Iterative Multiple Model Estimation (GIMME) algorithm
Scientific career
Fields	Neuroscience Quantitative psychology
Institutions	University of North Carolina
Thesis	Novel estimation method for arriving at group connectivity maps with fMRI data
Doctoral advisors	Michael Rovine Peter Molenaar

Kathleen Marie "Katie" Gates is an American neuroscientist, quantitative psychologist, and faculty member in the L. L. Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill. She is known for her contributions to network analysis, time series analysis, and structural equation modeling toward the elucidation of intraindividual change.

She is the inventor of GIMME, an algorithm for finding mathematical models of psychophysiological processes across time.

Career

A native of Troy, Michigan, Gates earned a bachelor's degree from Michigan State University, a master's degree in forensic psychology from the John Jay College of Criminal Justice at the City University of New York, and a PhD in Human Development and Family Studies with a focus in quantitative methods from Pennsylvania State University. She joined the Psychology and Neuroscience faculty at the University of North Carolina in 2013.

She is an elected member of the Society of Multivariate Experimental Psychology.

Research

Gates publishes statistical methods for the analysis of intensive longitudinal data. She is the recipient of a grant from the National Institute of Biomedical Imaging and Bioengineering to study connectivity maps from functional magnetic resonance imaging.

Selected publications

• Gates, K. M., & Liu, S. (2016). Methods for quantifying patterns of dynamic interactions in dyads. Assessment, 23(4), 459–471.
• Gates, K. M., Gatzke‐Kopp, L. M., Sandsten, M., & Blandon, A. Y. (2015). Estimating time‐varying RSA to examine psychophysiological linkage of marital dyads. Psychophysiology, 52(8), 1059–1065.
• Gates, K. M., Molenaar, P. C., 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.
• Gates, K. M., & Molenaar, P. C. (2012). Group search algorithm recovers effective connectivity maps for individuals in homogeneous and heterogeneous samples. NeuroImage, 63(1), 310–319.
• Gates, K. M., Molenaar, P. C., Hillary, F. G., & Slobounov, S. (2011). Extended unified SEM approach for modeling event-related fMRI data. NeuroImage, 54(2), 1151–1158.
• Gates, K. M., Molenaar, P. C., 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.

External links

• Gates Research Group
• Kathleen Gates's profile on Google Scholar
• gimme: Group Iterative Multiple Model Estimation (CRAN)