18 citations · 87 across the 23 of their papers we have counts for
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stat.AP2019★ 10 cited
On Post-Selection Inference in A/B Tests
Alex Deng, Yicheng Li, Jiannan Lu +1
When interpreting A/B tests, we typically focus only on the statistically significant results and take them by face value. This practice, termed post-selection inference in the sta…
stat.ME2019
Sharp bounds on the relative treatment effect for ordinal outcomes
Jiannan Lu, Yunshu Zhang, Peng Ding
For ordinal outcomes, the average treatment effect is often ill-defined and hard to interpret. Echoing Agresti and Kateri (2017), we argue that the relative treatment effect can be…
stat.AP2019
On Heavy-user Bias in A/B Testing
Yu Wang, Somit Gupta, Jiannan Lu +2
On-line experimentation (also known as A/B testing) has become an integral part of software development. To timely incorporate user feedback and continuously improve products, many…