Gladen B C
National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA.
Int J Epidemiol. 1996 Apr;25(2):420-5. doi: 10.1093/ije/25.2.420.
If pair members are independent, simple matched-pair case-control studies are known to yield consistent estimates of the population odds ratio. If pair members are not independent, this is not necessarily true. It has been shown previously that the usual matched-pair estimate remains consistent if the exposure of interest is correlated within the pairs. However, the effect of correlation of unmeasured risk factors within the pairs has not been studied.
We examine the effect of within-pair correlation of unmeasured risk factors independent of the measured exposure. This is done within the context of a simple matched-pair case-control study. We compare the large-sample expectation of the usual matched-pair estimate to the population odds ratio.
We show that the usual estimate may be inconsistent in the presence of this correlation. However, if the disease is rare, the magnitude of the bias will be negligible.
Correlation of unmeasured risk factors independent of the measured exposure is not a practical problem in this setting.
如果配对成员相互独立,已知简单匹配对病例对照研究能够得出总体优势比的一致估计值。如果配对成员不独立,情况未必如此。此前已经表明,如果感兴趣的暴露在配对中具有相关性,那么常用的匹配对估计值仍然是一致的。然而,配对中未测量的风险因素的相关性影响尚未得到研究。
我们研究了与测量暴露无关的未测量风险因素在配对中的相关性影响。这是在简单匹配对病例对照研究的背景下进行的。我们将常用匹配对估计值的大样本期望值与总体优势比进行比较。
我们表明,在存在这种相关性的情况下,常用估计值可能不一致。然而,如果疾病罕见,偏差的大小将可以忽略不计。
与测量暴露无关的未测量风险因素的相关性在这种情况下不是一个实际问题。