A Comparison of Some Approximate Confidence Intervals for a Single Proportion for Clustered Binary Outcome Data
A Comparison of Some Approximate Confidence Intervals for a Single Proportion for Clustered Binary Outcome Data
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DOI：
10.1515/ijb-2015-0024
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发表时间：
2016-11-01
影响因子：
1.2
通讯作者：
Wang, Suojin
中科院分区：
文献类型：
--
作者：
Saha, Krishna K.;Miller, Daniel;Wang, Suojin
聚类分析中二元结果数据分析中比例参数的区间估计在许多生物医学应用中经常是一个重要的问题。在本文中，我们提出了两种方法的基础上的轮廓似然和威尔逊得分。我们将它们与两种现有的方法进行比较，推荐用于复杂的调查数据和其他一些方法，这些方法是众所周知的方法的简单扩展，如可能性，Zeger和Liang的广义估计方程和Rao和Scott的比率估计方法。一个广泛的模拟研究进行各种参数组合的目的，评估和比较这些方法的性能方面的覆盖范围和预期的长度。生物医学数据的应用程序被用来说明所提出的方法。
Interval estimation of the proportion parameter in the analysis of binary outcome data arising in cluster studies is often an important problem in many biomedical applications. In this paper, we propose two approaches based on the profile likelihood and Wilson score. We compare them with two existing methods recommended for complex survey data and some other methods that are simple extensions of well-known methods such as the likelihood, the generalized estimating equation of Zeger and Liang and the ratio estimator approach of Rao and Scott. An extensive simulation study is conducted for a variety of parameter combinations for the purposes of evaluating and comparing the performance of these methods in terms of coverage and expected lengths. Applications to biomedical data are used to illustrate the proposed methods.