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{{more footnotes|date=April 2012}}
In [[statistics]], '''restricted randomization''' occurs in the [[design of experiments]] and in particular in the context of [[randomized experiment]]s and [[randomized controlled trial]]s. Restricted randomization allows intuitively poor allocations of treatments to experimental units to be avoided, while retaining the theoretical benefits of randomization.<ref>{{cite book|last1=Dodge|first1=Y.|title=The Oxford Dictionary of Statistical Terms|publisher=OUP|year=2006|isbn=978-0-19-920613-1|url-access=registration|url=https://archive.org/details/oxforddictionary0000unse}}</ref><ref>{{cite journal|last1=Grundy|first1=P.M.|last2=Healy|first2=M.J.R.|author-link2=Michael Healy (statistician)|title=Restricted randomization and quasi-Latin squares|journal=Journal of the Royal Statistical Society, Series B|date=1950 |volume=12|issue=2 |pages=286–291 |doi=10.1111/j.2517-6161.1950.tb00062.x }}</ref> 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|date=November 2012}} and [[William J. Youden]] (1972){{full citation needed|date=November 2012}} "as a way of avoiding bad spatial patterns of treatments in designed experiments."<ref name="ref1">{{Cite journal |jstor = 2288775|title = Restricted Randomization: A Practical Example|last1 = Bailey|first1 = R. A.|journal = Journal of the American Statistical Association|year = 1987|volume = 82|issue = 399|pages = 712–719|doi = 10.1080/01621459.1987.10478487}}</ref>
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