3 papers
stat.ME2020
Reducing Interference Bias in Online Marketplace Pricing Experiments
David Holtz, Ruben Lobel, Inessa Liskovich +1
Online marketplace designers frequently run A/B tests to measure the impact of proposed product changes. However, given that marketplaces are inherently connected, total average tr…
stat.AP2020
Limiting Bias from Test-Control Interference in Online Marketplace Experiments
David Holtz, Sinan Aral
In an A/B test, the typical objective is to measure the total average treatment effect (TATE), which measures the difference between the average outcome if all users were treated a…
cs.SI2020
The Engagement-Diversity Connection: Evidence from a Field Experiment on Spotify
David Holtz, Benjamin Carterette, Praveen Chandar +3
It remains unknown whether personalized recommendations increase or decrease the diversity of content people consume. We present results from a randomized field experiment on Spoti…