Thompson sampling

Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health

Digital mental health (DMH) interventions, such as text-message-based lessons and activities, offer immense potential for accessible mental health support. While these interventions can be effective, real-world experimental testing can further …

Multinomial Thompson sampling for rating scales and prior considerations for calibrating uncertainty

Bandit algorithms such as Thompson sampling (TS) have been put forth for decades as useful tools for conducting adaptively-randomised experiments. By skewing the allocation toward superior arms, they can substantially improve particular outcomes of …

Multinomial Thompson Sampling for Online Sequential Decision Making with Rating Scales (Invited Seminar @ Federico II di Napoli)

Multi-armed bandit algorithms such as Thompson sampling (TS) have been put forth for decades as useful tools for optimizing sequential decision-making in online experiments. By skewing the allocation ratio towards superior arms, they can minimize …

Adaptive Experiments for Enhancing Digital Education -- Benefits and Statistical Challenges (Talk @ ICNA-STA2023)

Adaptive digital field experiments are continually increasing in their breadth of use in fields like mobile health and digital education. Using adaptive experimentation in education can help not only to explore and eventually compare various arms but …

Daily Motivational Text Messages to Promote Physical Activity in University Students: Results From a Microrandomized Trial

Low physical activity is an important risk factor for common physical and mental disorders. Physical activity interventions delivered via smartphones can help users maintain and increase physical activity, but outcomes have been mixed. Here we …