How does randomization work?

• Researchers, for a variety of reasons, require randomization. First, there should be no systematic differences between individuals in different groups. If treatment groups are systematically different in a clinical study, the findings will be biased. Assume that participants are divided into control and treatment groups in research evaluating the efficacy of a walking intervention. If the treatment group has a higher number of older persons, the outcome of the walking intervention may be altered by this imbalance. The treatment’s effects would be indistinguishable from the influence of covariate imbalance, necessitating the researcher to account for covariates in the analysis.

• Each participant in the pair was randomly allocated to one of two groups: control or treatment. Researchers use randomization to give each participant an equal chance of being allocated to one of the groups, eliminating potential bias and making the groups similar to the dependent variable. Indeed, in clinical studies, randomization of treatments is the only way to eliminate characteristic systematic bias among subjects randomized to different treatments. Although a simple coin flip can be used for randomization, more appropriate and superior approaches are frequently required, especially in small clinical studies.
• For the random assignment of participants to treatment groups in clinical trials, many approaches have been proposed. Standard randomization approaches are discussed in this article, including essential randomization, block randomization, stratified randomization, and covariate adaptive randomization. Each approach is detailed in detail, along with its benefits and drawbacks. It’s critical to choose a method that produces both interpretable and valid data for your research.

References

Kang M, Ragan BG, Park JH. Issues in outcomes research: an overview of randomization techniques for clinical trials. J Athl Train. 2008;43(2):215-221. doi:10.4085/1062-6050-43.2.215