|Title||VC-BART: Bayesian trees for varying coefficients|
|Year of Publication||2020|
|Authors||Deshpande, SK, Bai, R, Balocchi, C, Starling, JE, Weiss, J|
|Keywords||Cognition, Methodology, socioeconomics|
Many studies have reported associations between later-life cognition and socioeconomic position in childhood, young adulthood, and mid-life. However, the vast majority of these studies are unable to quantify how these associations vary over time and with respect to several demographic factors. Varying coefficient (VC) models, which treat the covariate effects in a linear model as nonparametric functions of additional effect modifiers, offer an appealing way to overcome these limitations. Unfortunately, state-of-the-art VC modeling methods require computationally prohibitive parameter tuning or make restrictive assumptions about the functional form of the covariate effects.