Padieu R
Rev Epidemiol Sante Publique. 1981;29(3):255-68.
Trials often consist in comparing two samples, or more, which have been differently treated. Often these two samples are obtained by choosing individuals at random. Yet it may be easier, or even unavoidable, to randomize groups rather than individuals. It this case, the accuracy of estimates, that is the significance level of tests is different. In order to evaluate them, it is necessary to take into account a possible "cluster effect". On the basis of the two-stage sampling theory, it is possible to build a Student-like test. Nevertheless, the convergence towards a Student variable is slower than in the case of an individual randomization. Thus, the approximation cannot always be accepted. Aside from this question of how to build a correct test, the fact is that randomization by group most often means a loss of efficiency. The loss may result from the homogeneity of the clusters, from their unequal sizes and from the fact that the degrees of freedom are fewer. Sometimes, one can limit the loss by using a sampling technique which at least takes into account the sizes of the clusters.
试验通常包括比较两个或更多经过不同处理的样本。通常这两个样本是通过随机选择个体获得的。然而，对组而非个体进行随机化可能更容易，甚至是不可避免的。在这种情况下，估计的准确性，即检验的显著性水平是不同的。为了评估它们，有必要考虑可能的“聚类效应”。基于两阶段抽样理论，可以构建一个类似学生氏检验的检验。然而，向学生氏变量的收敛比个体随机化的情况要慢。因此，这种近似并不总是能被接受。除了如何构建正确检验的这个问题之外，事实上按组随机化通常意味着效率的损失。这种损失可能源于聚类的同质性、它们大小不等以及自由度较少的事实。有时，可以通过使用至少考虑聚类大小的抽样技术来限制这种损失。
