2 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
When Representative Samples Produce Worse Outcomes: Scale-up Decisions and Testing in Small-Budget RCTs
Hannah Li, Hongseok Namkoong, Isaac Scheinfeld
Small randomized controlled trials are often used to screen interventions before running larger follow-up studies. This is a critical phase of experimentation, as missing effective…
Deployment of AI-Assisted Interventions: Capacity Constraints and Noisy Compliance
Carri W. Chan, Yi Han, Hannah Li +1
AI tools increasingly guide targeted interventions in healthcare, education, and recruiting. Algorithms score individuals, trigger outreach to those above a threshold (e.g., high-r…
Operational Dosage: Implications of Capacity Constraints for the Design and Interpretation of Experiments
Justin Boutilier, Jonas Oddur Jonasson, Hannah Li +1
We study RCTs that evaluate the impact of service interventions, for example, teachers or advisors conducting proactive outreach to at-risk students, medical providers giving medic…
When Does Interference Matter? Decision-Making in Platform Experiments
Ramesh Johari, Hannah Li, Anushka Murthy +1
This paper investigates decision-making in A/B experiments for online platforms and marketplaces. In such settings, due to constraints on inventory, A/B experiments typically lead…