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二元整群抽样下共同比值比的估计

Estimation of a common odds ratio under binary cluster sampling.

作者信息

Ahn C, Odom-Maryon T

机构信息

Department of biostatistics, City of Hope Medical Center, Duarte, CA 91010, USA.

出版信息

Stat Med. 1995 Jul 30;14(14):1567-76. doi: 10.1002/sim.4780141407.

Abstract

We present results from a simulation study for the estimation of a common odds ratio in multiple 2 x 2 tables when the data are correlated within clusters. We model the correlation of the data by the beta-binomial distribution. Through a simulation study, we compare the Mantel-Haenszel estimator with Rao and Scott's estimator in terms of their biases, observed variances, relative efficiencies of their variances and 95 per cent coverage proportions. We limit the simulation study to the case where there are the same number of subjects in each cluster and the same number of observations in each row of each stratum. When rho = 0, we recommend use of the Mantel-Haenszel estimator gamma MH with an unadjusted variance and Rao and Scott's estimator gamma RSP with a pooled design effect. In general, when rho > 0, we recommend the Mantel-Haenszel estimator gamma MH with an adjusted variance and Rao and Scott's estimator gamma RSP with a pooled design effect.

摘要

我们展示了一项模拟研究的结果,该研究用于估计多个2×2表格中的共同优势比,此时数据在聚类内具有相关性。我们通过β-二项分布对数据的相关性进行建模。通过模拟研究,我们在偏差、观察到的方差、方差的相对效率以及95%的覆盖比例方面,比较了Mantel-Haenszel估计量与Rao和Scott的估计量。我们将模拟研究限制在每个聚类中受试者数量相同且每个层的每行中观察值数量相同的情况。当ρ = 0时,我们建议使用具有未调整方差的Mantel-Haenszel估计量γMH和具有合并设计效应的Rao和Scott估计量γRSP。一般来说,当ρ > 0时,我们建议使用具有调整方差的Mantel-Haenszel估计量γMH和具有合并设计效应的Rao和Scott估计量γRSP。

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