False Discovery in A/B Testing

False Discovery in A/B Testing

Abstract:

We investigate what fraction of all significant results in website A/B testing is actually null effects (i.e., the false discovery rate (FDR)). Our data consist of 4,964 effects from 2,766 experiments conducted on a commercial A/B testing platform. Using three different methods, we find that the FDR ranges between 28% and 37% for tests conducted at 10% significance and between 18% and 25% for tests at 5% significance (two sided). These high FDRs stem mostly from the high fraction of true null effects, about 70%, rather than from low power. Using our estimates, we also assess the potential of various A/B test designs to reduce the FDR. The two main implications are that decision makers should expect one in five interventions achieving significance at 5% confidence to be ineffective when deployed in the field and that analysts should consider using two-stage designs with multiple variations rather than basic A/B tests.

More information on Ron Berman can be found here.

The Seminar will be held in Seminar Room RuW 1.201 as well as broadcasted via Zoom with the following link:

https://uni-frankfurt.zoom.us/j/62958556058?pwd=b01qWXlrbVMzc1JFVEhjSWNvdGZPQT09

Meeting-ID: 629 5855 6058
Kenncode: 101686