A comparison between traditional methods and multilevel regression for the analysis of multicenter intervention studies
A comparison between traditional methods and multilevel regression for the analysis of multicenter intervention studies
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DOI：
10.1016/s0895-4356(03)00007-6
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发表时间：
2003-04-01
影响因子：
7.2
通讯作者：
Berger, MP
中科院分区：
文献类型：
--
作者：
Moerbeek, M;van Breukelen, GJP;Berger, MP
本文综述了三种传统的多中心试验分析方法，即，中心，即朴素回归（人作为分析单位），固定效应回归，并使用汇总措施（集群作为分析单位），并比较这些方法与多水平回归。比较是针对连续（定量）结果进行的，并且基于治疗效果及其标准误的估计值，因为这些通常是干预研究的主要兴趣。当实验结果必须对一些较大的中心人群有效时，干预研究中的中心必须提供来自该人群的随机样本，并且可以使用多水平回归。它表明，治疗效果，特别是它的标准误差，通常是不正确的估计，由传统的方法，因此，不应该在一般情况下被用作替代多水平回归。(C)2003年爱思唯尔公司All rights reserved.
This article reviews three traditional methods for the analysis of multicenter trials with persons nested within clusters, i.e., centers, namely naive regression (persons as units of analysis), fixed effects regression, and the use of summary measures (clusters as units of analysis), and compares these methods with multilevel regression. The comparison is made for continuous (quantitative) outcomes, and is based on the estimator of the treatment effect and its standard error, because these usually are of main interest in intervention studies. When the results of the experiment have to be valid for some larger population of centers, the centers in the intervention study have to present a random sample from this population and multilevel regression may be used. It is shown that the treatment effect and especially its standard error, are generally incorrectly estimated by the traditional methods, which should, therefore, not in general be used as an alternative to multilevel regression. (C) 2003 Elsevier Inc. All rights reserved.