Statistical inference for correlated data in ophthalmologic studies
Statistical inference for correlated data in ophthalmologic studies
复制标题
眼科研究中相关数据的统计推断
DOI：
10.1002/sim.2425
复制
发表时间：
2006-08-30
影响因子：
2
通讯作者：
Rosner, Bernard
中科院分区：
文献类型：
--
作者：
Tang, Man-Lai;Tang, Nian-Sheng;Rosner, Bernard
在眼科研究中，每个受试者通常为两只眼睛中的每一只提供重要信息，并且两只眼睛的值通常高度相关。先前的研究表明，忽略组内相关性的二元配对数据的检验程序可能会导致显著性水平的膨胀。此外，这是可能的，渐近版本的这些程序，考虑到组内相关性也可能产生不可接受的高I型错误率时，样本量小或数据结构稀疏。我们提出了两种替代方案，即精确无条件和近似无条件的程序。根据我们的模拟结果，精确的程序通常会产生非常保守的经验I型错误率。也就是说，相应的I类错误率可能会大大低估预先指定的标称水平（例如（经验I类错误率/标称I类错误率）0.8）。另一方面，近似无条件程序通常产生接近预先选择的标称水平的经验I类错误率。我们说明我们的方法与数据集从视网膜脱离的研究。版权所有© 2005年约翰威利父子有限公司。
In ophthalmologic studies, each subject usually contributes important information for each of two eyes and the values from the two eyes are generally highly correlated. Previous studies showed that test procedures for binary paired data that ignore the presence of intraclass correlation could lead to inflated significance levels. Furthermore, it is possible that asymptotic versions of these procedures that take the intraclass correlation into account could also produce unacceptably high type I error rates when the sample size is small or the data structure is sparse. We propose two alternatives for these situations, namely the exact unconditional and approximate unconditional procedures. According to our simulation results, the exact procedures usually produce extremely conservative empirical type I error rates. That is, the corresponding type I error rates could greatly underestimate the pre‐assigned nominal level (e.g. (empirical type I error rate/nominal type I error rate) 0.8). On the other hand, the approximate unconditional procedures usually yield empirical type I error rates close to the pre‐chosen nominal level. We illustrate our methodologies with a data set from a retinal detachment study. Copyright © 2005 John Wiley & Sons, Ltd.