ArticlePloS one2018
The impact of selection bias in randomized multi-arm parallel group clinical trials.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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Who cites it
10 citing papers in PubMed.
- Evaluation of a Technology-Based Multifactorial Intervention for Improving Fall Risk: A Cluster-Randomized Controlled Trial.Research square · 2026Article
- Reducing selection bias risk to enhance RCT validity: sandwich mixed randomization outperforms permuted block design.BMC medical research methodology · 2026Article
- Does randomization matter in rare disease clinical trials.PloS one · 2026Article
- The impact of allocation bias on test decisions in clinical trials with multiple endpoints using multiple testing strategies.BMC medical research methodology · 2024Article
- Intervention Tournaments: An Overview of Concept, Design, and Implementation.Perspectives on psychological science : a journal of the Association for Psychological Science · 2022Article
- Emerging biomaterial-based strategies for personalized therapeutic in situ cancer vaccines.Biomaterials · 2022Review
- Echocardiographic assessment of functional mitral regurgitation: opening Pandora's box?ESC heart failure · 2019Article
- Randomization in survival studies: An evaluation method that takes into account selection and chronological bias.PloS one · 2019Article
- Implementing Optimal Designs for Dose-Response Studies Through Adaptive Randomization for a Small Population Group.The AAPS journal · 2018Article
- Lessons learned from IDeAl - 33 recommendations from the IDeAl-net about design and analysis of small population clinical trials.Orphanet journal of rare diseases · 2018Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The impact of selection bias on the results of clinical trials has been analyzed extensively for trials of two treatments, yet its impact in multi-arm trials is still unknown. In this paper, we investigate selection bias in multi-arm trials by its impact on the type I error probability. We propose two models for selection bias, so-called biasing policies, that both extend the classic guessing strategy by Blackwell and Hodges. We derive the distribution of the F-test statistic under the misspecified outcome model and provide a formula for the type I error probability under selection bias. We apply the presented approach to quantify the influence of selection bias in multi-arm trials with increasing number of treatment groups using a permuted block design for different assumptions and different biasing strategies. Our results confirm previous findings that smaller block sizes lead to a higher proportion of sequences with inflated type I error probability. Astonishingly, our results also show that the proportion of sequences with inflated type I error probability remains constant when the number of treatment groups is increased. Realizing that the impact of selection bias cannot be completely eliminated, we propose a bias adjusted statistical model and show that the power of the statistical test is only slightly deflated for larger block sizes.
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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.