Robustness of parameter and standard error estimates against ignoring a contextual effect of a subject-level covariate in cluster-randomized trials
Robustness of parameter and standard error estimates against ignoring a contextual effect of a subject-level covariate in cluster-randomized trials
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DOI：
10.3758/s13428-011-0094-8
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发表时间：
2011-12-01
影响因子：
5.4
通讯作者：
Maas, Cora J. M.
中科院分区：
文献类型：
--
作者：
Korendijk, Elly J. H.;Hox, Joop J.;Maas, Cora J. M.
在实验研究中，将星团分配给条件并不少见。在分析这种分组随机试验的数据时，应采用多水平分析，以便考虑到第二水平单元(即，分组)内第一水平单位(即受试者)之间的相关性。此外，多水平分析可以处理两个水平上的协变量。如果涉及第一级协变量，通常会估计该协变量的簇内效应，隐含地假设上下文效应相等。然而，这一假设可能会被违反。当前模拟研究的重点是忽略簇内效应和背景协变量效应的不等性对处理效应的参数和标准误差估计的影响，这是实验研究中主要感兴趣的参数。我们发现，忽略簇内效应和上下文效应的不等性并不影响对治疗效果或其标准误差的估计。然而，方差分量的估计以及常量的标准误差被发现是有偏见的。
In experimental research, it is not uncommon to assign clusters to conditions. When analysing the data of such cluster-randomized trials, a multilevel analysis should be applied in order to take into account the dependency of first-level units (i.e., subjects) within a second-level unit (i.e., a cluster). Moreover, the multilevel analysis can handle covariates on both levels. If a first-level covariate is involved, usually the within-cluster effect of this covariate will be estimated, implicitly assuming the contextual effect to be equal. However, this assumption may be violated. The focus of the present simulation study is the effects of ignoring the inequality of the within-cluster and contextual covariate effects on parameter and standard error estimates of the treatment effect, which is the parameter of main interest in experimental research. We found that ignoring the inequality of the within-cluster and contextual effects does not affect the estimation of the treatment effect or its standard errors. However, estimates of the variance components, as well as standard errors of the constant, were found to be biased.