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This practical guide is designed for students and researchers with an existing knowledge of R who wish to learn how to apply it in an epidemiological context and exploit its versatility. It also serves as a broader introduction to the quantitative aspects of modern practical epidemiology.
Table des matières
- Preface
- Introduction
- 1: Using R
- 2: Measures of disease occurrence
- 3: Prevalence data- models, likelihood and binomial regression
- 4: Regression models
- 5: Analysis of follow-up data
- 6: Parametrization and prediction of rates
- 7: Case-control and case-cohort studies
- 8: Survival analysis
- 9: Do not group quantitative variables
A propos de l'auteur
Bendix Carstensen is a Senior Statistician in Clinical Epidemiology at the Steno Diabetes Center, Gentofte and an External Lecturer at the Department of Biostatistics, University of Copenhagen, Denmark. His expertise and interests are chiefly in the areas of Biostatistics, Epidemiology/Public Health and Diabetes Epidemiology.
Résumé
This practical guide is designed for students and researchers with an existing knowledge of R who wish to learn how to apply it in an epidemiological context and exploit its versatility. It also serves as a broader introduction to the quantitative aspects of modern practical epidemiology.
Texte suppl.
This volume will be useful to epidemiologists who are looking for a quick reference guide on how to practically use R in epidemiological research, particularly the Epi and survival packages.
