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三种比值比近似置信限方法的性能。

The performance of three approximate confidence limit methods for the odds ratio.

作者信息

Gart J J, Thomas D G

出版信息

Am J Epidemiol. 1982 Mar;115(3):453-70. doi: 10.1093/oxfordjournals.aje.a113323.

DOI:10.1093/oxfordjournals.aje.a113323
PMID:7064980
Abstract

The performance of three approximate confidence limit methods for the odds ratio, R, is studied at the 95% level in the unconditional sample space. There are: the method proposed by Cornfield (Proceedings of the 3rd Berkeley Symposium 1956;4:135-48), the logit method with 1/2 corrections first considered by Woolf (Ann Hum Genet 1955;19:251-3), and the test-based method proposed by Miettinen (Am J Epidemiol 1976;103:226-35). Cornfield's method comes closest to attaining the normal confidence coefficient. The logit method typically has actual confidence coefficients somewhat too large with disparate tail areas. The latter is ascribed in part to the enhanced skewness induced by the logit transformation itself. The test-based method has actual coefficients uniformly less than nominal when R not equal to 1. This underestimation is worse in finite samples than Halperin found it to be asymptotically. Although the Cornfield and test-based methods have the same confidence coefficients for R = 1, the test-based method is more likely to cover distant values of R not equal to 1 when in fact R = 1. It is concluded that Cornfield's method without the continuity correction is the preferred approximate method in the unconditional space as, with the continuity correction, it was previously found to be in the conditional space.

摘要

在无条件样本空间中,研究了比值比(R)的三种近似置信限方法在95%水平下的性能。这三种方法分别是:Cornfield提出的方法(《第三届伯克利研讨会论文集》,1956年;4:135 - 48)、Woolf首次考虑的带有1/2校正的对数单位法(《人类遗传学杂志》,1955年;19:251 - 3)以及Miettinen提出的基于检验的方法(《美国流行病学杂志》,1976年;103:226 - 35)。Cornfield方法最接近达到正态置信系数。对数单位法的实际置信系数通常在不同的尾部区域有些过大。后者部分归因于对数单位变换本身所导致的偏度增强。当(R\neq1)时,基于检验的方法的实际系数始终小于名义系数。在有限样本中,这种低估比Halperin发现的渐近情况更严重。尽管当(R = 1)时,Cornfield方法和基于检验的方法具有相同的置信系数,但当实际上(R = 1)时,基于检验的方法更有可能涵盖不等于1的(R)的较远值。结论是,在无条件空间中,不进行连续性校正的Cornfield方法是首选的近似方法,就像之前发现在条件空间中进行连续性校正时它是首选方法一样。

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