Intermediate and advanced topics in multilevel logistic regression analysis

• Published in: Statistics in medicine Vol. 36; no. 20; pp. 3257 - 3277
• Main Authors: Austin, Peter C., Merlo, Juan
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 10.09.2017; John Wiley and Sons Inc
• Subjects: Analysis of Variance; Biostatistics; Cluster Analysis; clustered data; Data Interpretation, Statistical; Health risk assessment; Health Sciences; Heart attacks; hierarchical models; Humans; Hälsovetenskap; Logistic Models; logistic regression; Matematik; Mathematical Sciences; Mathematics; Medical and Health Sciences; Medical statistics; Medicin och hälsovetenskap; multilevel analysis; multilevel models; Myocardial Infarction - mortality; Natural Sciences; Naturvetenskap; Odds Ratio; Probability Theory and Statistics; Regression analysis; Sannolikhetsteori och statistik; Tutorial in Biostatistics; clustered data; multilevel analysis; hierarchical models; logistic regression; multilevel models

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...