6 citations · 10 across the 7 of their papers we have counts for
11 papers · 1 filter
Alternative statistical inference for the first normalized incomplete moment
Jiannan Lu, Peng Ding, Anqi Zhao
This paper re-examines the first normalized incomplete moment, a well-established measure of inequality with wide applications in economic and social sciences. Despite the populari…
Privacy-preserving Quantile Treatment Effect Estimation for Randomized Controlled Trials
Leon Yao, Paul Yiming Li, Jiannan Lu
In accordance with the principle of "data minimization", many internet companies are opting to record less data. However, this is often at odds with A/B testing efficacy. For exper…
All about sample-size calculations for A/B testing: Novel extensions and practical guide
Jing Zhou, Jiannan Lu, Anas Shallah
While there exists a large amount of literature on the general challenges of and best practices for trustworthy online A/B testing, there are limited studies on sample size estimat…
The equivalence of the Delta method and the cluster-robust variance estimator for the analysis of clustered randomized experiments
Alex Deng, Jiannan Lu, Wen Qin
It often happens that the same problem presents itself to different communities and the solutions proposed or adopted by those communities are different. We take the case of the va…
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…
Improved Neymanian analysis for factorial designs with binary outcomes
Jiannan Lu
factorial designs are widely adopted by statisticians and the broader scientific community. In this short note, under the potential outcomes framework (Neyman, 1923; Rubin, 1…