Recommendations for choosing an analysis method that controls Type I error for unbalanced cluster sample designs with Gaussian outcomes.
Recommendations for choosing an analysis method that controls Type I error for unbalanced cluster sample designs with Gaussian outcomes.
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DOI：
10.1002/sim.6565
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发表时间：
2015-11-30
影响因子：
2
通讯作者：
Glueck, Deborah H.
中科院分区：
文献类型：
--
作者：
Johnson, Jacqueline L.;Kreidler, Sarah M.;Catellier, Diane J.;Murray, David M.;Muller, Keith E.;Glueck, Deborah H.
我们使用基于理论和模拟的方法来研究聚类随机设计的一阶段和两阶段分析方法的I型错误率。单阶段方法使用观察到的数据作为结果，并使用一般线性混合模型解释集群内的相关性。两阶段模型使用聚类特定均值作为一般线性单变量模型中的结果。我们分析表明，一阶段和两阶段的模型实现精确的I型错误率时，集群大小是相等的。对于不平衡数据，不存在精确的大小α检验，并且可能发生I型错误膨胀。通过模拟，我们比较了四个一阶段和六个两阶段的假设检验方法对不平衡数据的I类错误率。对于不平衡数据，两阶段模型，由聚类均值的估计理论方差的倒数加权，方差约束为正值，为每组至少有6个聚类的研究提供了最佳的I类错误控制。Roger自由度和无约束方差在每组至少有14个聚类的研究中表现良好。阶段模型与分母自由度适当的平衡数据表现不佳的小样本量和低集群内的相关性。由于小样本量和低群内相关性是群集随机试验的共同特征，Kenward-Roger方法是首选的一阶段方法。
We used theoretical and simulation-based approaches to study Type I error rates for one-stage and two-stage analytic methods for cluster-randomized designs. The one-stage approach uses the observed data as outcomes, and accounts for within cluster correlation using a general linear mixed model. The two-stage model uses the cluster specific means as the outcomes in a general linear univariate model. We demonstrate analytically that both one-stage and two-stage models achieve exact Type I error rates when cluster sizes are equal. With unbalanced data, an exact size α test does not exist and Type I error inflation may occur. Via simulation, we compare the Type I error rates for four one-stage and six two-stage hypothesis testing approaches for unbalanced data. With unbalanced data, the two-stage model, weighted by the inverse of the estimated theoretical variance of the cluster means, and with variance constrained to be positive, provided the best Type I error control for studies having at least 6 clusters per arm. The one-stage model with Kenward-Roger degrees of freedom and unconstrained variance performed well for studies having at least 14 clusters per arm. The popular analytic method of using a one-stage model with denominator degrees of freedom appropriate for balanced data performed poorly for small sample sizes and low intracluster correlation. Since small sample sizes and low intracluster correlation are common features of cluster-randomized trials, the Kenward-Roger method is the preferred one-stage approach.
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影响因子：
3.7
作者：
DEMPSTER, AP;RUBIN, DB;TSUTAKAWA, RK
通讯作者：
TSUTAKAWA, RK
DOI：
10.1111/j.2517-6161.1977.tb01600.x
发表时间：
1977-01-01
期刊：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL
影响因子：
--
作者：
DEMPSTER, AP;LAIRD, NM;RUBIN, DB
通讯作者：
RUBIN, DB
影响因子：
1.9
作者：
LAIRD, NM;WARE, JH
通讯作者：
WARE, JH
影响因子：
1.9
作者：
Kenward, MG;Roger, JH
通讯作者：
Roger, JH
影响因子：
2.2
作者：
Crespi, Catherine M.;Maxwell, Annette E.;Wu, Sheng
通讯作者：
Wu, Sheng