ArticleProceedings of the National Academy of Sciences of the United States of America2022
On the number of trials needed to distinguish similar alternatives.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Refining a multimedia patient-reported outcomes measure for patients with low literacy.Journal of patient-reported outcomes · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A/B testing is widely used to tune search and recommendation algorithms, to compare product variants as efficiently and effectively as possible, and even to study animal behavior. With ongoing investment, due to diminishing returns, the items produced by the new alternative B show smaller and smaller improvement in quality from the items produced by the current system A. By formalizing this observation, we develop closed-form analytical expressions for the sample efficiency of a number of widely used families of slate-based comparison tests. In empirical trials, these theoretical sample complexity results are shown to be predictive of real-world testing efficiency outcomes. These findings offer opportunities for both more cost-effective testing and a better analytical understanding of the problem.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.