BREAKING THE MATCHES IN A PAIRED T-TEST FOR COMMUNITY INTERVENTIONS WHEN THE NUMBER OF PAIRS IS SMALL
BREAKING THE MATCHES IN A PAIRED T-TEST FOR COMMUNITY INTERVENTIONS WHEN THE NUMBER OF PAIRS IS SMALL
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DOI：
10.1002/sim.4780141309
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发表时间：
1995-07-15
影响因子：
2
通讯作者：
CHEADLE, A
中科院分区：
文献类型：
--
作者：
DIEHR, P;MARTIN, DC;CHEADLE, A
社区是促进健康的实验单位，因此对社区促进健康的干预有相当大的兴趣。由于这种干预措施费用高昂，因此试点单位(社区)的数量通常较少。由于所涉及的社区数量较少，研究人员经常在随机化之前将治疗和对照社区在人口统计学变量上进行匹配，以将严重分裂的可能性降至最低。不幸的是，配对已被证明在配对数量较少时会降低设计的能力，除非匹配变量与结果变量高度相关(在这种情况下，与健康行为的变化)。我们使用计算机模拟来检查一种方法的性能，在该方法中，我们匹配了社区，但执行了不匹配的分析。如果合适的匹配变量未知，且不到10对，则不匹配的设计和分析具有最大的威力。然而，如果一个人更喜欢匹配设计，那么对于N<；10，可以通过执行匹配数据的非匹配分析来增加功率。我们还讨论了该过程的一种变体，在该过程中，只有在匹配“不起作用”的情况下才执行不匹配分析。
There is considerable interest in community interventions for health promotion, where the community is the experimental unit. Because such interventions are expensive, the number of experimental units (communities) is usually small. Because of the small number of communities involved, investigators often match treatment and control communities on demographic variables before randomization to minimize the possibility of a bad split. Unfortunately, matching has been shown to decrease the power of the design when the number of pairs is small, unless the matching variable is very highly correlated with the outcome variable (in this case, with change in the health behaviour). We used computer simulation to examine the performance of an approach in which we matched communities but performed an unmatched analysis. If the appropriate matching variables are unknown, and there are fewer than ten pairs, an unmatched design and analysis has the most power. If, however, one prefers a matched design, then for N < 10, power can be increased by performing an unmatched analysis of the matched data. We also discuss a variant of this procedure, in which an unmatched analysis is performed only if the matching 'did not work'.