A comparison of confidence interval methods for the intraclass correlation coefficient in cluster randomized trials
A comparison of confidence interval methods for the intraclass correlation coefficient in cluster randomized trials
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DOI：
10.1002/sim.1330
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发表时间：
2002-12-30
影响因子：
2
通讯作者：
Ukoumunne, OC
中科院分区：
文献类型：
--
作者：
Ukoumunne, OC
本研究比较了为类内相关系数（rho）的方差估计量分析分配置信区间的不同方法。比较的背景是在计划聚类随机试验时使用rho来估计方差膨胀因子。采用蒙特卡罗模拟非平衡聚类数据和聚类随机试验数据对两种方法进行比较，该试验旨在改善全科医院哮喘管理的干预措施。比较了不同簇数、每簇平均受试者数和rho基础值下数据的区间覆盖率和精度。对于具有正态分布和非正态分布群集特定效应的数据，还比较了这些方法的性能。模拟结果表明，基于方差比统计量的方法比基于大样本近似rho标准误差的方法提供了更大的覆盖水平。Searle的方法为具有正态分布随机效应的数据提供了接近名义覆盖率的数据。Searle方法的调整版本允许数据缺乏平衡，但无论在覆盖范围还是精度方面都没有改进。然而，对试验数据的分析表明，当算术均值与调和均值聚类大小明显不同时，Thomas和Hultquist方法提供的限制可能与其他方差比统计方法的限制不同。仿真结果表明，在聚类水平的随机效应中，显著的非正态性影响了所有方法的性能。相对于rho的基本大小，这些方法的置信区间通常较宽，这表明在随机化的大型集群试验中，样本大小计算可能存在很大的不确定性。样本大小比典型的随机试验大得多的基于聚类研究的数据需要以合理的精度估计rho。版权所有:John Wiley Sons, Ltd。
This study compared different methods for assigning confidence intervals to the analysis of variance estimator of the intraclass correlation coefficient (rho). The context of the comparison was the use of rho to estimate the variance inflation factor when planning cluster randomized trials. The methods were compared using Monte Carlo simulations of unbalanced clustered data and data from a cluster randomized trial of an intervention to improve the management of asthma in a general practice setting. The coverage and precision of the intervals were compared for data with different numbers of clusters, mean numbers of subjects per cluster and underlying values of rho. The performance of the methods was also compared for data with Normal and non-Normally distributed cluster specific effects. Results of the simulations showed that methods based upon the variance ratio statistic provided greater coverage levels than those based upon large sample approximations to the standard error of rho. Searle's method provided close to nominal coverage for data with Normally distributed random effects. Adjusted versions of Searle's method to allow for lack of balance in the data generally did not improve upon it either in terms of coverage or precision. Analyses of the trial data, however, showed that limits provided by Thomas and Hultquist's method may differ from those of the other variance ratio statistic methods when the arithmetic mean differs markedly from the harmonic mean cluster size. The simulation results demonstrated that marked non-Normality in the cluster level random effects compromised the performance of all methods. Confidence intervals for the methods were generally wide relative to the underlying size of rho suggesting that there may be great uncertainty associated with sample size calculations for cluster trials where large clusters are randomized. Data from cluster based studies with sample sizes much larger than those typical of cluster randomized trials are required to estimate rho with a reasonable degree of precision. Copyright (C) 2002 John Wiley Sons, Ltd.