ArticleJournal of biopharmaceutical statistics2017
A novel evaluation of optimality for randomized controlled trials.
Article in Journal of biopharmaceutical statistics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- A case study in teaching and learning the design, conduction, and analysis of Bayesian adaptive trials through an application.Journal of clinical and translational science · 2026Article
- Exploring Bayesian adaptive designs in multi-arm randomized controlled trials with a patient preference arm.Journal of biopharmaceutical statistics · 2025Article
- The value of a two-armed Bayesian response adaptive randomization trial.Journal of biopharmaceutical statistics · 2023Article
- Comparative Effectiveness Research using Bayesian Adaptive Designs for Rare Diseases: Response Adaptive Randomization Reusing Participants.Statistics in biopharmaceutical research · 2023Article
- Using Adaptive Designs to Avoid Selecting the Wrong Arms in Multiarm Comparative Effectiveness Trials.Statistics in biopharmaceutical research · 2019Article
- Hyperbaric oxygen brain injury treatment (HOBIT) trial: a multifactor design with response adaptive randomization and longitudinal modeling.Pharmaceutical statistics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Balanced two-arm designs are more powerful than unbalanced designs and, consequently, Bayesian adaptive designs (BADs) are less powerful. However, when considering other subject- or community-focused design characteristics, fixed two-arm designs can be suboptimal. We use a novel approach to identify the best two-arm study design, taking into consideration both the statistical perspective and the community's perception. Data envelopment analysis (DEA) was used to estimate the relative performance of competing designs in the presence of multiple optimality criteria. The two-arm fixed design has enough deficiencies in subject- and community-specific benefit to make it the least favorable study design.
Indexed as
Identifiers
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.