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In statistics, restricted randomization occurs in the design of experiments and in particular in the context of randomized experiments and randomized controlled trials. Restricted randomization allows intuitively poor allocations of treatments to experimental units to be avoided, while retaining the theoretical benefits of randomization.[1][2] For example, in a clinical trial of a new proposed treatment of obesity compared to a control, an experimenter would want to avoid outcomes of the randomization in which the new treatment was allocated only to the heaviest patients.
The concept was introduced by Frank Yates (1948)[full citation needed] and William J. Youden (1972)[full citation needed] "as a way of avoiding bad spatial patterns of treatments in designed experiments."[3]
- ^ Dodge, Y. (2006). The Oxford Dictionary of Statistical Terms. OUP. ISBN 978-0-19-920613-1.
- ^ Grundy, P.M.; Healy, M.J.R. "Restricted randomization and quasi-Latin squares". Journal of the Royal Statistical Society, Series B. 12: 286–291.
- ^ Bailey, R. A. (1987). "Restricted Randomization: A Practical Example". Journal of the American Statistical Association. 82 (399): 712–719. doi:10.1080/01621459.1987.10478487. JSTOR 2288775.