Simon Vandekar's work develops theoretically justified methods and software that are directly applicable in another scientific field. He is interested in applications in psychiatry, psychology, neuroimaging, and ecology.
My work develops theoretically justified methods and software that are directly applicable in another scientific field. My interests include developing tools to address challenges in analyzing data sets from the fields of psychology, psychiatry, and medical imaging. I utilize statistical tools such as generalized additive models, latent variable models, multilevel models, semiparametric methods, estimating equations, and machine learning. My latest statistical research focuses on robust inference procedures for high-dimensional spatial data (with a focus on neuroimaging) and semiparametric methods for model selection, effect size, and replicability.