Centering or Not Centering in Multilevel Models? The Role of the Group Mean and the Assessment of Group Effects
Centering or Not Centering in Multilevel Models? The Role of the Group Mean and the Assessment of Group Effects
复制标题
多级模型中居中还是不居中？
作者：
O. Paccagnella
在多水平回归中，将模型变量居中会产生与传统回归分析不同的效果，有时甚至是意想不到的效果。在这篇文章中，主要贡献的意义，假设和影响的基础上的一个多层次的中心解决方案进行审查，强调这种方法的优点和批评。此外，在Manski的精神，上下文和相关的影响，在一个多层次的框架被定义为检测群体效应。它表明，在多层次分析的中心的决定取决于变量的方式为中心，在该模型是否已指定有或没有跨层次的条款和组的手段，以及具体分析的目的。
In multilevel regression, centering the model variables produces effects that are different and sometimes unexpected compared with those in traditional regression analysis. In this article, the main contributions in terms of meaning, assumptions, and effects underlying a multilevel centering solution are reviewed, emphasizing advantages and critiques of this approach. In addition, in the spirit of Manski, contextual and correlated effects in a multilevel framework are defined to detect group effects. It is shown that the decision of centering in a multilevel analysis depends on the way the variables are centered, on whether the model has been specified with or without cross-level terms and group means, and on the purposes of the specific analysis.