The prevention and handling of the missing data
Open accessAbstract
Even in a well-designed and controlled study, missing data occurs in almost all research. Missing data can reduce the statistical power of a study and can produce biased estimates, leading to invalid conclusions. This manuscript reviews the problems and types of missing data, along with the techniques for handling missing data. The mechanisms by which missing data occurs are illustrated, and the methods for handling the missing data are discussed. The paper concludes with recommendations for the handling of missing data.
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Missing data can impact the sensitivity of the study and lead to biased estimates, distorted power, and loss of information if the missing values are not random.
“Missing data, common in all areas of research, can impact the sensitivity of the study and also lead to biased estimates, distorted power, and loss of information if the missing values are not random [54].”
From Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0 (2020) · cites this paper as [54]
The Abstract (page not provided) says missing data reduce statistical power and can bias parameter estimates; the Missing completely at random section adds that power can be lost even when estimates remain unbiased. The paper also describes lost data, but it does not say missing data affect the study’s sensitivity. Its Sensitivity analysis section discusses a method for testing the robustness of results, not a loss of study sensitivity. (LLM, conf=0.84)
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References 18 · Cited by 1,728
Research works printed but not linked: 8
- [1]Graham JW Missing data analysis: making it work in the real world Annu Rev Psychol 2009 60 549 576 18652544
- [2]Little RJ D'Agostino R Cohen ML Dickersin K Emerson SS Farrar JT The prevention and treatment of missing data in clinical trials N Engl J Med 2012 367 1355 1360 23034025 PMC3771340
- [3]O'Neill RT Temple R The prevention and treatment of missing data in clinical trials: an FDA perspective on the importance of dealing with it Clin Pharmacol Ther 2012 91 550 554 22318615
- [6]Wisniewski SR Leon AC Otto MW Trivedi MH Prevention of missing data in clinical research studies Biol Psychiatry 2006 59 997 1000 16566901
- [7]Scharfstein DO Hogan J Herman A On the prevention and analysis of missing data in randomized clinical trials: the state of the art J Bone Joint Surg Am 2012 94 Suppl 1 80 84 22810454 PMC3393113
- [8]Wilcox S Shumaker SA Bowen DJ Naughton MJ Rosal MC Ludlam SE Promoting adherence and retention to clinical trials in special populations: a women's health initiative workshop Control Clin Trials 2001 22 279 289 11384790
- [13]Panel on Missing Data in Clinical Trials The prevention and treatment of missing data in clinical trials 2010 2nd ed Washington DC National Academies Press 107 114 24983040
- [15]Sinharay S Stern HS Russell D The use of multiple imputation for the analysis of missing data Psychol Methods 2001 6 317 329 11778675
- Authors
- Kang, H.
- Affiliations
- Chung-Ang University (KR)
- Corresponding author
- Kang, Hyun
- ORCID
- Kang, Hyun
- Venue
- Korean Journal of Anesthesiology
- Published
- 2013
- Volume
- 64
- Issue
- 5
- Pages
- 402
- ISSN
- 0302-5780 (ISSN-L)
- 2005-6419
- 2005-7563
- PMC
- PMC3668100
- OpenAlex
- W1977098485
- Cited by
- 1,728
- References
- 18
- Citations by year
- 2026: 148 · 2025: 242 · 2024: 251 · 2023: 225 · 2022: 255 · 2021: 238 · 2020: 171 · 2019: 98 · 2018: 58 · 2017: 23 · 2016: 12 · 2015: 3 · 2014: 2
- FWCI
- 5.00
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Korean Journal of Anesthesiology (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- missing data, missing data mechanisms, missing data handling, statistical power, missing data imputation, research design
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