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Issues in Outcomes Research: An Overview of Randomization Techniques for Clinical Trials
Open accessAbstract
Objective: To review and describe randomization techniques used in clinical trials, including simple, block, stratified, and covariate adaptive techniques. Background: Clinical trials are required to establish treatment efficacy of many athletic training procedures. In the past, we have relied on evidence of questionable scientific merit to aid the determination of treatment choices. Interest in evidence-based practice is growing rapidly within the athletic training profession, placing greater emphasis on the importance of well-conducted clinical trials. One critical component of clinical trials that strengthens results is random assignment of participants to control and treatment groups. Although randomization appears to be a simple concept, issues of balancing sample sizes and controlling the influence of covariates a priori are important. Various techniques have been developed to account for these issues, including block, stratified randomization, and covariate adaptive techniques. Advantages: Athletic training researchers and scholarly clinicians can use the information presented in this article to better conduct and interpret the results of clinical trials. Implementing these techniques will increase the power and validity of findings of athletic medicine clinical trials, which will ultimately improve the quality of care provided.
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“First of all, one of the limitations may be the selected randomization method which was chosen to simply control balance across groups over time for a sample size of 60 participants. As published data suggest, the 6-block randomization method may not be optimal for randomization, as blocks are best used in smaller increments due to easier balance control. Therefore, the 4-block randomization”
From Early Occupational Therapy Intervention post-stroke (EOTIPS): A randomized controlled trial (2024) · cites this paper as [69]
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“Primarily, the small sample size hinders the generalizability of the results, underscoring the need for a larger sample for a more robust analysis [27] and regarding the statistical inaccuracy of using Cohen’s d for sample size calculation with a binary outcome (PONV incidence).”
Leung, J., Keller, E., Nietert, P. J., Caldwell, T., Dismuke, C., Johnson, H., & Williams, E. M. (2025) · Lupus Science & Medicine · doi:10.1136/lupus-2025-001712
Seeing the bigger picture – a comparison between 2D and 360°-AR action observation in golf training
Schumacher, T., & Klatt, S. (2025) · International Journal of Sport and Exercise Psychology · doi:10.1080/1612197x.2025.2578864
Shrestha, N., Simkhada, P. P., Kurmi, O., Gautam, S., Karmacharya, B. M., Shrestha, A., Tamrakar, R., & Poudel, A. N. (2025) · PLoS ONE · doi:10.1371/journal.pone.0335333 · Cited by 1
“A simple randomization technique [57] will be used to assign participants to either intervention or control group on 1:1 basis.”
Metadata
- Authors
- Kang, M., Ragan, B. G., & Park, J.-H.
- Affiliations
- Middle Tennessee State University (US)
- University of Northern Iowa (US)
- Korea National Sport University (KR)
- Venue
- Journal of Athletic Training
- Published
- 2008-03
- Volume
- 43
- Issue
- 2
- Pages
- 215-221
- ISSN
- 1062-6050 (ISSN-L)
- PMC
- PMC2267325
- OpenAlex
- W2103799103
- Semantic Scholar
- 76a894a7f31f671125792589418911fc63574599
- Cited by
- 555
- References
- 31
- Citations by year
- 2026: 54 · 2025: 79 · 2024: 90 · 2023: 54 · 2022: 29 · 2021: 33 · 2020: 39 · 2019: 22 · 2018: 26 · 2017: 27 · 2016: 20 · 2015: 16 · 2014: 17 · 2013: 12 · 2012: 15
- FWCI
- 6.61
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Athletic Training (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UNI ScholarWorks (University of Northern Iowa) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- randomization technique, clinical trials, block randomization, stratified randomization, covariate-adaptive randomization, covariate control, evidence-based practice
- MeSH terms
- Clinical Trials as Topic, Female, Humans, Male, Random Allocation, Outcome Assessment, Health Care, Evidence-Based Medicine
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