Differential dropout and bias in randomised controlled trials: when it matters and when it may not
Open accessAbstract
Dropout in randomised controlled trials is common and threatens the validity of results, as completers may differ from people who drop out. Differing dropout rates between treatment arms is sometimes called differential dropout or attrition. Although differential dropout can bias results, it does not always do so. Similarly, equal dropout may or may not lead to biased results. Depending on the type of missingness and the analysis used, one can get a biased estimate of the treatment effect with equal dropout rates and an unbiased estimate with unequal dropout rates. We reinforce this point with data from a randomised controlled trial in patients with renal cancer and a simulation study.
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Dropout in research typically diminishes the validity of results, as completers may differ from people who drop out.
“Dropout in research typically diminishes the validity of results, as completers may differ from people who drop out [30].”
From Analysis of Mobile App-Based Mental Health Solutions for College Students: A Rapid Review (2023) · cites this paper as [30]
The Abstract says dropout in randomised controlled trials threatens validity because completers may differ from those who drop out. But the claim extends this to research generally and says validity is typically diminished; the Introduction and Discussion explain that dropout does not always produce biased results. (LLM, conf=0.85)
Experimental — accuracy not yet measuredBell et al. determined that equal number of drop-outs rates do not guarantee unbiased results in RCTs.
“A similar drop-out rate for different treatments arms is often seen as a reassurance against bias; however, Bell et al. determined that equal number of drop-outs rates do not guarantee unbiased results in RCTs [21].”
From Checklist to assess Trustworthiness in RAndomised Controlled Trials (TRACT checklist): concept proposal and pilot (2023) · cites this paper as [21]
Differential dropout can reduce the validity of findings if completers differ from those who drop out.
“Differential dropout can reduce the validity of findings if completers differ from those who drop out [39].”
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“Differential dropout can reduce the validity of findings if completers differ from those who drop out [39].”
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- Authors
- Bell, M. L., Kenward, M. G., Fairclough, D. L., & Horton, N. J.
- Affiliations
- The University of Sydney (AU)
- London School of Hygiene & Tropical Medicine (GB)
- University of Colorado Denver (US)
- Smith College (US)
- Corresponding author
- Bell, M. L.
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2013-01-21
- Volume
- 346
- Issue
- jan21 1
- Pages
- e8668-e8668
- ISSN
- 1756-1833 (ISSN-L)
- PMC
- PMC4688419
- OpenAlex
- W2063185787
- Cited by
- 460
- References
- 24
- Citations by year
- 2026: 49 · 2025: 58 · 2024: 64 · 2023: 50 · 2022: 45 · 2021: 46 · 2020: 34 · 2019: 28 · 2018: 23 · 2017: 13 · 2016: 13 · 2015: 12 · 2014: 15 · 2013: 9
- FWCI
- 14.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- BMJ (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (CA-05826, P01CA005826)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- attrition bias, missing data, randomized controlled trials, treatment effect estimation, missing data mechanisms, kidney cancer, simulation study
- MeSH terms
- Humans, Patient Dropouts, Randomized Controlled Trials as Topic
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