cjbart

A tool for analyzing conjoint experiments using Bayesian Additive Regression Trees ('BART'), a machine learning method developed by Chipman, George and McCulloch (2010) doi:10.1214/09-AOAS285. This tool focuses specifically on estimating, identifying, and visualizing the heterogeneity within marginal component effects, at the observation- and individual-level. It uses a variable importance measure ('VIMP') with delete-d jackknife variance estimation, following Ishwaran and Lu (2019) doi:10.1002/sim.7803, to obtain bias-corrected estimates of which variables drive heterogeneity in the predicted individual-level effects.