Adaptive sampling and hypotheses testing to identify the best nudge in factorial experiments

Brown Bag Seminar
Speaker
Date
Wednesday 29 Jun 2022, 12:00 - 13:00
Type
Seminar
Location

Online

Registration Add to calendar

In offline or crowdsourced web experiments, behavioral scientists and consumer researchers often want to identify the intervention with largest effect size. This is sometimes done with highly dimensional factorial designs, such as  megastudies of nudges.

Current practice consists of randomising factors across observations. This is often underpowered - failing to identify the best intervention - and always inefficient - by administering suboptimal factors too often.

Adaptive factorial designs

In this research I introduce a methodology for adaptive factorial designs to identify the best factor. The methodology leverages recently introduced algorithms in machine learning and operations research to adaptively allocate each factor. Furthermore, the methodology allows researchers to stop data collection once sufficient evidence has been collected, without pre-specifying the sample size.

Simulation experiments show large gains over standard randomisation as well as overperforming alternative algorithms. A few extensions deal with interaction effects and multiple hypotheses testing. A Python package automatises the methodology via Qualtrics, facilitating easy implementation in practice. 

Registration Brown Bag Seminar

I am interested in a brown bag seminar:
Deadline for registration is on the Friday (before 17:00) preceding the Brown Bag Seminar on Thursday.
Enter a date in the format: 09-08-2022

 
Fields marked with an * are required.

Privacy Statement

Erasmus School of Economics handles your (registration) information confidentially. Your data will only be used for logistical purposes. More information can be found on www.eur.nl/en/ese/disclaimer/privacy-statement.

More information

Please confirm your attendance as soon as possible by because of catering.

Related links
Department of Economics

Compare @count study programme

  • @title

    • Duration: @duration
Compare study programmes