The effect of matching on the power of randomized community intervention studies.
Currently, there is considerable interest in studies that use the community as the experimental unit. Health promotion programmes are one example. Because such activities are expensive, the number of experimental units (communities) is usually very small. Investigators often match communities on demographic variables in order to improve the power of their studies. Matching is known to improve power in certain circumstances. However, we show here that if the number of communities is small, the matched design will probably have less power than the unmatched design. This is due primarily to the loss of degrees of freedom in the matched design, which outweighs the benefits of matching on any but the strongest correlates of changes in behaviour. In the community intervention situation, even small differences in sample size between the matched and unmatched analyses can have expensive consequences.
Martin
D C
DC
Department of Biostatistics, University of Washington, Seattle 98195.
Diehr
P
P
Perrin
E B
EB
Koepsell
T D
TD
D015982:Bias; D003153:Community Health Services / Q000592:standards*; D015987:Effect Modifier, Epidemiologic; D006293:Health Promotion / Q000592:standards*; D006801:Humans; D016555:Matched-Pair Analysis; D015995:Prevalence; D011897:Random Allocation; D012107:Research Design / Q000592:standards*; D015983:Selection Bias; D012907:Smoking / Q000453:epidemiology; D016540:Smoking Cessation / Q000379:methods; D000074606:Smoking Prevention; D016896:Treatment Outcome