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Bayesian estimation of log odds ratios over two-way contingency tables with intraclass correlated cells

机译:类内相关单元的双向列联表的对数比值的贝叶斯估计

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摘要

In this article, a Bayesian approach is proposed for the estimation of log odds ratios and intraclass correlations over a two-way contingency table, including intraclass correlated cells. Required likelihood functions of log odds ratios are obtained, and determination of prior structures is discussed. Hypothesis testing for log odds ratios and intraclass correlations by using the posterior simulations is outlined. Because the proposed approach includes no asymptotic theory, it is useful for the estimation and hypothesis testing of log odds ratios in the presence of certain intraclass correlation patterns. A family health status and limitations data set is analyzed by using the proposed approach in order to figure out the impact of intraclass correlations on the estimates and hypothesis tests of log odds ratios. Although intraclass correlations are small in the data set, we obtain that even small intraclass correlations can significantly affect the estimates and test results, and our approach is useful for the estimation and testing of log odds ratios in the presence of intraclass correlations.
机译:在本文中,提出了一种贝叶斯方法,用于估计双向列联表中的对数比值比和类内相关性,包括类内相关单元。获得了对数优势比的所需似然函数,并讨论了先验结构的确定。概述了使用后验模拟进行对数优势比和类内相关性的假设检验。因为所提出的方法不包括渐近理论,所以它在存在某些类内相关模式的情况下对对数比值比的估计和假设测试很有用。使用提出的方法分析家庭健康状况和局限性数据集,以找出类别内相关性对对数比值比的估计和假设检验的影响。尽管类别内的相关性在数据集中很小,但我们认为,即使类别间的相关性很小,也会显着影响估计和测试结果,并且在存在类别间相关性的情况下,我们的方法可用于对数比值比的估计和测试。

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