Intermediate and advanced topics in multilevel logistic regression analysis

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of…

• HA
  Heart and Stroke Foundation of Canada
• IF
  Institute for Clinical Evaluative Sciences
• OM
  Ontario Ministry of Health and Long-Term Care
• V
  Vetenskapsrådet

  Awards: VR #2013-2484, 2013-2484
• CI
  Canadian Institutes of Health Research

  Awards: 86508, VR #2013-2484, MOP 86508