Year: 2013
Type: conference-paper
Abstract: Many online experiments exhibit dependence between users and items. For example, in online advertising, observations that have a user or an ad in common are likely to be associated. Because of this, even in experiments involving millions of subjects, the difference in mean outcomes between control and treatment conditions can have substantial variance. Previous theoretical and simulation results demonstrate that not accounting for this kind of dependence structure can result in confidence intervals that are too narrow, leading to inaccurate hypothesis tests.
Authors: Eytan Bakshy, Dean Eckles
Institution: Meta (United States)
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4298081798