Modeling Multilevel Data Structures

作者：Marco R. Steenbergen, Bradford Jones · 发表于：American Journal of Political Science · 年份：2002 · DOI：10.2307/3088424 · 被引用次数：1522 · 研究领域：Electoral Systems and Political Participation、Gender Politics and Representation、Political Influence and Corporate Strategies

data are becoming quite common in political science and provide numerous opportunities for theory testing and development. Unfortunately this type of data typically generates a number of statistical problems, of which clustering is particularly impor? tant. To exploit the opportunities of? fered by multilevel data, and to solve the statistical problems inherent in them, special statistical techniques are required. In this article, we focus on a technique that has become popular in educational statistics and sociology?multilevel analysis. In multilevel analysis, researchers build models that capture the layered structure of multilevel data, and determine how layers interact and impact a dependent variable of interest. Our objective in this article is to introduce the logic and statistical theory behind multilevel models, to illustrate how such models can be applied fruitfully in political science, and to call atten? tion to some of the pitfalls in multilevel analysis.