Bayesian adaptive design benefits study subjects by allocating them to more effective treatment arms¶

Claim · All claims
Evidence · 1 study · theoretical r? · q2
Currency · newest study 2018 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Bayesian adaptive design benefits study subjects by assigning them to more effective treatment arms as evidence accumulates. → Mariel McKenzie Finucane 2018

Evidence¶

Mariel McKenzie Finucane 2018¶

Mariel McKenzie Finucane, Ignacio Martinez, Scott Cody. (2018). What Works for Whom? A Bayesian Approach to Channeling Big Data Streams for Public Program Evaluation. American Journal of Evaluation, vol. 39, issue 1. https://journals.sagepub.com/loi/aje doi:10.1177/1098214017737173

q2 · i? · theoretical · r?

The article's key findings list states this subject-level benefit of the adaptive design, in which "more study subjects are allocated to treatment arms that are more promising, given the specific subgroup from which each subject comes". No effect size is printed.

"Bayesian adaptive design benefits study subjects by assigning them to more effective treatment arms."

Discussion¶

Related Claims¶

• Bayesian adaptive design benefits evaluators by allowing smaller and more informative studies — related
• A Bayesian adaptive design can yield superior inference to a standard design using less than one third the sample size under identified conditions — related
• The adaptive trial design reallocates more study subjects to more promising treatment arms as evidence accumulates — possibly the same claim (merge candidate)
• The Bayesian adaptive design can produce better inference and ultimately smaller trials under identifiable conditions — related
• The multi-step grading recipe with calibration examples achieves the highest scoring accuracy and receives the majority of bandit arm pulls — related