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English
Oxford University Press
31 December 2020
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.

The standard tools used in epidemiology are described and the practical use of R for these is clearly explained and laid out. R code examples, many with output, are embedded throughout the text. The entire code is also available on the companion website so that readers can reproduce all the results and graphs featured in the book.

Epidemiology with R is an advanced textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners in the fields of human and non-human epidemiology, public health, veterinary science, and biostatistics.

By:  
Imprint:   Oxford University Press
Country of Publication:   United Kingdom
Dimensions:   Height: 254mm,  Width: 195mm,  Spine: 19mm
Weight:   708g
ISBN:   9780198841326
ISBN 10:   0198841329
Pages:   256
Publication Date:  
Audience:   College/higher education ,  Primary
Format:   Hardback
Publisher's Status:   Active
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

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.

Reviews for Epidemiology with R

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. * Rose Saint Fleur-Calixte, Quarterly Review of Biology *


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