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使用横断面和重复测量数据估计的组内相关系数估计值和标准误差的比较:Safety Check 聚类随机试验。

Comparison of intraclass correlation coefficient estimates and standard errors between using cross-sectional and repeated measurement data: the Safety Check cluster randomized trial.

机构信息

Department of Biostatistical Sciences and Department of Social Sciences and Health Policy, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27012, USA.

出版信息

Contemp Clin Trials. 2011 Mar;32(2):225-32. doi: 10.1016/j.cct.2010.11.001. Epub 2010 Nov 8.

Abstract

Designing cluster randomized trials in clinical studies often requires accurate estimates of intraclass correlation, which quantifies the strength of correlation between units, such as participants, within a cluster, such as a practice. Published ICC estimates, even when available, often suffer from the problem of wide confidence intervals. Using data from a national, randomized, controlled study concerning violence prevention for children--the Safety Check--we compare the ICC values derived from two approaches only baseline data and using both baseline and follow-up data. Using a variance component decomposition approach, the latter method allows flexibility in handling complex data sets. For example, it allows for shifts in the outcome variable over time and for an unbalanced cluster design. Furthermore, we evaluate the large-sample formula for ICC estimates and standard errors using the bootstrap method. Our findings suggest that ICC estimates range from 0.012 to 0.11 for providers within practice and range from 0.018 to 0.11 for families within provider. The estimates derived from the baseline-only and repeated-measurements approaches agree quite well except in cases in which variation over repeated measurements is large. The reductions in the widths of ICC confidence limits from using repeated measurement over baseline only are, respectively, 62% and 42% at the practice and provider levels. The contribution of this paper therefore includes two elements, which are a methodology for improving the accuracy of ICC, and the reporting of such quantities for pediatric and other researchers who are interested in designing clustered randomized trials similar to the current study.

摘要

在临床研究中设计群组随机试验通常需要准确估计组内相关系数,该系数量化了群组(如实践)内单位(如参与者)之间的相关性强度。即使有已发表的 ICC 估计值,它们的置信区间也往往很宽。我们使用来自一项全国性、随机对照研究(儿童暴力预防安全检查)的数据,比较了仅基线数据和同时使用基线和随访数据两种方法得出的 ICC 值。使用方差分量分解方法,后一种方法允许灵活处理复杂数据集。例如,它允许因变量随时间变化以及集群设计不平衡。此外,我们使用自举法评估 ICC 估计值和标准误差的大样本公式。我们的研究结果表明,提供者内的 ICC 估计值范围为 0.012 至 0.11,提供者内的家庭的 ICC 估计值范围为 0.018 至 0.11。仅基线和重复测量方法得出的估计值非常吻合,除非重复测量的变异较大。与仅基线重复测量相比,ICC 置信限的宽度分别减少了 62%和 42%,在实践和提供者层面上。因此,本文的贡献包括两个方面,即提高 ICC 准确性的方法和为有兴趣设计类似于当前研究的群组随机试验的儿科和其他研究人员报告这些数量。

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