A Nonparametric Bayesian Analysis of Heterogenous Treatment Effects in Digital Experimentation
数字实验中异质性处理效应的非参数贝叶斯分析
Randomized controlled trials play an important role in how Internet companies predict the impact of policy decisions and product changes. In these “digital experiments,” different units (people, devices, products) respond differently to the treatment. This article presents a fast and scalable Bayesian nonparametric analysis of such heterogenous treatment effects and their measurement in relation to observable covariates. New results and algorithms are provided for…