Full Description
This open access book is a practical introduction to multilevel modelling or multilevel analysis (MLA) - a statistical technique being increasingly used in public health and health services research. The authors begin with a compelling argument for the importance of researchers in these fields having an understanding of MLA to be able to judge not only the growing body of research that uses it, but also to recognise the limitations of research that did not use it. The volume also guides the analysis of real-life data sets by introducing and discussing the use of the multilevel modelling software MLwiN, the statistical package that is used with the example data sets. Importantly, the book also makes the training material accessible for download - not only the datasets analysed within the book, but also a freeware version of MLwiN to allow readers to work with these datasets.
The book's practical review of MLA comprises:
Theoretical, conceptual, and methodological background
Statistical background
The modelling process and presentation of research
Tutorials with example datasets
Multilevel Modelling for Public Health and Health Services Research: Health in Context is a practical and timely resource for public health and health services researchers, statisticians interested in the relationships between contexts and behaviour, graduate students across these disciplines, and anyone interested in utilising multilevel modelling or multilevel analysis.
"Leyland and Groenewegen's wealth of teaching experience makes this book and its accompanying tutorials especially useful for a practical introduction to multilevel analysis."
̶ Juan Merlo, Professor of Social Epidemiology, Lund University
"Comprehensive and insightful. A must for anyone interested in the applications of multilevel modelling to population health".
̶ S. (Subu) V.Subramanian, Professor of Population Health and Geography, Harvard University
Contents
Part I: Theoretical, conceptual and methodological background.- Chapter 1: Introduction.- Chapter 2: Health in context.- Chapter 3: What is multilevel modelling?.- Chapter 4: Multilevel data structures.- Part II: Statistical background.- Chapter 5: Graphs and equations.- Chapter 6: Apportioning variation in multilevel models.- Part III: The modelling process and presentation of research.- Chapter 7: Context, composition and how their influences vary.- Chapter 8: Ecometrics: Using MLA to construct contextual variables from individual data.- Chapter 9: Modelling strategies.- Chapter 10: Reading and writing.- Part IV: Tutorials with example datasets.- Chapter 11: Multilevel linear regression using MLwiN: Mortality in England and Wales, 1979-1992.- Chapter 12. Multilevel logistic regression using MLwiN: Referrals to physiotherapy.- Chapter 13. Untangling context and composition using MLwiN: Incidence of cardiovascular disease in small areas in Scotland.
