A confidence interval approach to sample size estimation for interobserver agreement studies with multiple raters and outcomes
A confidence interval approach to sample size estimation for interobserver agreement studies with multiple raters and outcomes
复制标题
DOI：
10.1016/j.jclinepi.2011.10.019
复制
发表时间：
2012-07-01
影响因子：
7.2
通讯作者：
Donner, Allan
中科院分区：
文献类型：
--
作者：
Rotondi, Michael A.;Donner, Allan
目的：测量观察者间一致性(可靠性)的研究在临床实践中很常见，但仍在讨论合适的样本量估计。与临床试验相比，技术是最小的。作者提出了一种样本量估计技术，以在观察者间一致性研究中获得预先指定的kappa系数可信区间的下限和上限。研究设计和背景：所提出的技术可用于设计一项测量观察者间一致性的研究，该研究具有任意数量的结果和任意数量的评分者。潜在的应用领域包括：病理学、精神病学、牙科和物理疗法。结果：通过两个例子说明了该技术。第一项是口腔放射学的一项初步研究，其作者研究了三位牙科专业人士测量的下颌骨皮质指数的可靠性。第二个例子考察了四名护士对加拿大分诊和敏锐度量表中使用的五种分诊水平的观察者间协议水平。结论：这种方法在观察者间协议研究的规划阶段应该是有用的，在该研究中，调查者希望在估计kappa时获得预先指定的精度水平。还提供了实现该方法的R软件包(奥地利维也纳的R统计计算基金会)kappaSize。(C)2012 Elsevier Inc.保留所有权利。
Objective: Studies measuring interobserver agreement (reliability) are common in clinical practice, yet discussion of appropriate sample size estimation. techniques is minimal as compared with clinical trials. The authors propose a sample size estimation technique to achieve a prespecified lower and upper limit for a confidence interval for the kappa coefficient in studies of interobserver agreement.Study Design and Setting: The proposed technique can be used to design a study measuring interobserver agreement with any number of outcomes and any number of raters. Potential application areas include: pathology, psychiatry, dentistry, and physical therapy.Results: This technique is illustrated using two examples. The first considers a pilot study in oral radiology, whose authors studied the reliability of the mandibular cortical index as measured by three dental professionals. The second example examines the level of interobserver agreement among four nurses with respect to five triage levels used in the Canadian Triage and Acuity Scale.Conclusion: This method should be useful in the planning stages of an interobserver agreement study in which the investigator would like to obtain a prespecified level of precision in the estimation of kappa. An R software package (R Foundation for Statistical Computing, Vienna, Austria), kappaSize is also provided that implements this Method. (C) 2012 Elsevier Inc. All rights reserved.