期刊
ANNUAL REVIEW OF PUBLIC HEALTH
卷 25, 期 -, 页码 53-77出版社
ANNUAL REVIEWS
DOI: 10.1146/annurev.publhealth.25.050503.153925
关键词
epidemiologic methods; hierarchical linear models; causation; cluster-randomized trials; empirical Bayes
Multilevel statistical models have become increasingly popular among public health researchers over the past decade. Yet the enthusiasm with which these models are being adopted may obscure rather than solve some problems of statistical and substantive inference. We discuss the three most common applications of multilevel models in public health: (a) cluster-randomized trials, (b) observational studies of the multilevel etiology of health and disease, and (c) assessments of health care provider performance. In each area of investigation, we describe how multilevel models are being applied, comment on the validity of the statistical and substantive inferences being drawn, and suggest ways in which the strengths of multilevel models might be more fully exploited. We conclude with a call for more careful thinking about multilevel causal inference.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据