research
∙
05/25/2023
All about sample-size calculations for A/B testing: Novel extensions and practical guide
While there exists a large amount of literature on the general challenge...
share
research
∙
03/17/2023
Feedback Effect in User Interaction with Intelligent Assistants: Delayed Engagement, Adaption and Drop-out
With the growing popularity of intelligent assistants (IAs), evaluating ...
research
∙
08/25/2022
Addressing Hidden Imperfections in Online Experimentation
Technology companies are increasingly using randomized controlled trials...
research
∙
05/31/2021
The equivalence of the Delta method and the cluster-robust variance estimator for the analysis of clustered randomized experiments
It often happens that the same problem presents itself to different comm...
research
∙
02/18/2021
Novelty and Primacy: A Long-Term Estimator for Online Experiments
Online experiments are the gold standard for evaluating impact on user e...
research
∙
10/09/2019
On Post-Selection Inference in A/B Tests
When a large number of simultaneous statistical inferences are conducted...
research
∙
07/24/2019
Sharp bounds on the relative treatment effect for ordinal outcomes
For ordinal outcomes, the average treatment effect is often ill-defined ...
research
∙
02/06/2019
Heavy User Effect in A/B Testing: Identification and Estimation
On-line experimentation (also known as A/B testing) has become an integr...
research
∙
03/16/2018
Applying the Delta method in metric analytics: A practical guide with novel ideas
During the last decade, the information technology industry has adopted ...
research
∙
03/12/2018
On improving Neymanian analysis for 2^K factorial designs with binary outcomes
2^K factorial designs are widely adopted by statisticians and the broade...
research
∙
03/12/2018
On finite-population Bayesian inferences for 2^K factorial designs with binary outcomes
Inspired by the pioneering work of Rubin (1978), we employ the potential...
research
∙
11/13/2017