xtgeebcv: A command for bias-corrected sandwich variance estimation for GEE analyses of cluster randomized trials.
xtgeebcv: A command for bias-corrected sandwich variance estimation for GEE analyses of cluster randomized trials.
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DOI：
10.1177/1536867x20931001
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发表时间：
2020-06
期刊：
影响因子：
--
通讯作者：
Turner EL
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文献类型：
--
作者：
Gallis JA;Li F;Turner EL
聚类随机试验通常用于评估公共卫生、教育和社会科学领域的干预措施，其中聚类（例如，学校或诊所）被随机分配到比较组，但测量对象是个体。分析通常是针对个人层面的结果进行的，这种分析方法必须考虑到同一集群成员的结果往往比其他集群成员的结果更相似。一种流行的个人分析技术是广义估计方程（GEE）。然而，通常随机化少量的集群（例如，30个或更少），在这种情况下，从三明治方差估计器获得的GEE标准误差将有偏差，导致膨胀的I型误差。已经提出并研究了一些偏差校正标准误差来解释这种有限样本偏差，但尚未在Stata中实施。在本文中，我们描述了几种常用的对鲁棒三明治方差的偏差修正。然后介绍我们新创建的命令xtgeebcv，它将允许Stata用户轻松地将有限样本修正应用于从GEE模型获得的标准误差。然后，我们提供示例来演示extgeebcv的使用。最后，我们讨论了在哪些情况下使用哪些有限样本修正的建议，并考虑了未来研究中可能提高xgeebcv的领域。
Cluster randomized trials, where clusters (for example, schools or clinics) are randomized to comparison arms but measurements are taken on individuals, are commonly used to evaluate interventions in public health, education, and the social sciences. Analysis is often conducted on individual-level outcomes, and such analysis methods must consider that outcomes for members of the same cluster tend to be more similar than outcomes for members of other clusters. A popular individual-level analysis technique is generalized estimating equations (GEE). However, it is common to randomize a small number of clusters (for example, 30 or fewer), and in this case, the GEE standard errors obtained from the sandwich variance estimator will be biased, leading to inflated type I errors. Some bias-corrected standard errors have been proposed and studied to account for this finite-sample bias, but none has yet been implemented in Stata. In this article, we describe several popular bias corrections to the robust sandwich variance. We then introduce our newly created command, xtgeebcv, which will allow Stata users to easily apply finite-sample corrections to standard errors obtained from GEE models. We then provide examples to demonstrate the use of xtgeebcv. Finally, we discuss suggestions about which finite-sample corrections to use in which situations and consider areas of future research that may improve xtgeebcv.
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DOI：
10.1136/bmj.d5886
发表时间：
2011-09-26
期刊：
BMJ (Clinical research ed.)
影响因子：
--
作者：
Ivers NM;Taljaard M;Dixon S;Bennett C;McRae A;Taleban J;Skea Z;Brehaut JC;Boruch RF;Eccles MP;Grimshaw JM;Weijer C;Zwarenstein M;Donner A
通讯作者：
Donner A
影响因子：
1.9
作者：
Lu, Bing;Preisser, John S.;Wolfson, Mark
通讯作者：
Wolfson, Mark
影响因子：
2
作者：
Li, Fan;Turner, Elizabeth L.;DeLong, Elizabeth R.
通讯作者：
DeLong, Elizabeth R.
影响因子：
2
作者：
Ford, Whitney P.;Westgate, Philip M.
通讯作者：
Westgate, Philip M.
影响因子：
1.9
作者：
Li, Fan;Turner, Elizabeth L.;Preisser, John S.
通讯作者：
Preisser, John S.