Book Review: Epidemiology: study design and data analysis, Second Edition

This book is, according to the preface, intended for two audiences: ‘the researcher who wishes to understand how statistical principles and techniques may be used to solve epidemiological problems, and the statistician who wishes to find out how to apply her or his subject in this field’. To this end the readers are only assumed to have a basic knowledge of statistics. This book contains 12 chapters, with a total of 114 subsections. Chapter 1 gives an introduction to epidemiology and defines the fundamental concepts used in epidemiology. Chapter 2 reviews the basic descriptive and inferential statistical techniques that are usually encountered when analysing epidemiological data. This thorough survey on 80 pages contains all the necessary statistical methods that are needed as background to understand the following 10 chapters, making the book selfcontained. The book should thus be accessible even for those without almost any statistical training. After the introduction and review in Chapters 1 and 2 the author continues in Chapters 3–8 with describing, and applying different methods for study designs and statistical analyses of epidemiological data to many examples. Chapter 3 is about the assessing of risk factors and, among other things, gives the merits of such concepts as relative risk and odds ratio and considers different tests of association between risk factor and disease. In Chapter 4 the concepts of confounding and interaction are treated. It gives methods for identifying and assessing confounders, dealing with it through standardization, estimation using Mantel–Haenszel methods and testing for interaction. Chapter 5 discusses the merits of cohort studies and methods for analysing these, such as cohort life tables and Kaplan–Meier estimation, as well as the person–years method. Chapter 6 deals with case–control studies, discusses the advantages and disadvantages of this study design, the methods of analysis for it and how the selection of cases and controls should be performed. It also deals with matching, nested case–control studies, case–cohort studies and case–crossover studies. In Chapter 7 intervention studies are treated and parallel group studies, crossover studies and sequential studies are discussed among other things. Chapter 8, finally, discusses the question of sample size determination, mainly concentrating on testing of mean values, difference between means, proportions and relative risks, and testing within case–control studies. After thus having discussed analysis methods for different study designs in Chapters 3–8, the author continues in Chapters 9–11 with a discussion of different statistical modelling approaches for epidemiological data. Chapter 9 discusses the modelling of quantitative outcome variables, mainly using oneway and two-way analysis-of-variance (ANOVA) and general linear models. Chapter 10 continues with discussing modelling binary outcome data, mainly using logistic regression. Chapter 11, finally, considers the modelling of survival data and discusses the usual parametric and semi-parametric regression models, such as the exponential and Weibull models and the Cox proportional hazards model, as well as others, such as the Weibull proportional hazards model, Poisson regression and pooled logistic regression. In contrast to the preceding eight chapters, where computer programs were not used, these three chapters contain outputs from SAS and discussions of the SAS procedures used. The use of SAS is, however, not the main focus of these chapters, and it is mainly used for the illustrating examples. Also, the SAS programs used are not given in the text but instead are available for download from the publisher’s website, together with the data sets used in the book. The final chapter, Chapter 12, contains a discussion of meta-analysis for epidemiological data. There are also three appendices about materials for the book available on the Internet with statistical tables and example data sets. The references contain 360 entries. This is an excellent book. It is well-written, easy to read, and covers everything in the field of epidemiology that can be desired. The focus is on understanding and applying statistical methods of epidemiology, and it gives all necessary mathematical formulas needed for calculations, but