False Discovery Rate Controlled Heterogeneous Treatment Effect Detection for Online Controlled Experiments
False Discovery Rate Controlled Heterogeneous Treatment Effect Detection for Online Controlled Experiments
Online controlled experiments (a.k.a. A/B testing) have been used as the mantra for data-driven decision making on feature changing and product shipping in many Internet companies. However, it is still a great challenge to systematically measure how every code or feature change impacts millions of users with great heterogeneity (e.g. …