2026-07-09 スタンフォード大学
＜関連情報＞
- https://news.stanford.edu/stories/2026/07/statistical-test-personalization-k-fold
- https://www.science.org/doi/10.1126/science.aeb9506
介入の個別化による効果を検証するための統計的検定 A statistical test for the benefits of personalizing interventions
Zhaoqi Li and Emma Brunskill
Science Published:9 Jul 2026
DOI:https://doi.org/10.1126/science.aeb9506
Estimating the value of personalization.
Abstract
From medicine to marketing to social sciences, the promise of tailoring interventions to individuals is undeniable. However, practical applications force weighing personalization’s potential benefits with its possible increased cost and fragility. We introduce a statistical hypothesis test that evaluates, given historical data, evidence that a personalized intervention policy’s performance will surpass deploying the best single intervention. The test maintains strict Type I error control while achieving asymptotic normality with the minimal possible variance under specified conditions. Results on diverse datasets from job training, depression treatment, education, and recommendation systems demonstrate the test’s versatility and its superior performance over alternatives. This test can support decision-makers throughout the intervention sciences by providing a simple and powerful quantification of the potential benefits of personalization.
