Restricted randomization: Difference between revisions

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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}}</ref><ref>{{cite journal|last1=Grundy|first1=P.M.|last2=Healy|first2=M.J.R.|authorlink2=Michael Healy (statistician)|title=Restricted randomization and quasi-Latin squares|journal=Journal of the Royal Statistical Society, Series B|volume=12|pages=286–291}}</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">Bailey, R. A. (1987) [https://www.jstor.org/discover/10.2307/2288775?uid=3739808&uid=2&uid=4&uid=3739256&sid=21100687318461 "Restricted Randomization: A Practical Example"], ''Journal of the American Statistical Association'', Vol. 82, No. 399 (Sep., 1987), pp. 712–719, at 712</ref>

==Example of nested data==

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==See also==

{{portalPortal|StatisticsMathematics}}

* [[Hierarchical linear modeling]]

* [[Mixed-design analysis of variance]]