Kristynn Sullivan is a doctoral candidate in quantitative psychology at the University of California, Merced. She received a B.S. in with honors psychology in 2009 from the University of Mary Washington in Fredericksburg, VA. Her research interests include modeling nonlinearity in longitudinal data. Specifically, she applies Generalized Additive Models - a regression technique that allows the level of non linearity to be estimated directly from the data - to short time series datasets. She also dabbles in meta-analysis, Bayesian modeling, and statistical consulting projects.