Statistical Tools for Epidemiologic Research

In this innovative new book, Steve Selvin provides readers with a clear understanding of intermediate biostatistical methods without advanced mathematical explanations or statistical theory (for example, no Bayesian statistics, no causal inference, no linear algebra, and only a slight hint of calculus). The book focuses on "second-year" techniques, providing a clear understanding of statistical techniques using symbols, data, examples, and graphics applied to case study data. This text answers the important question: After a typical first-year course in statistical methods, what next?

Statistical Tools for Epidemiologic Research thoroughly explains not just how statistical data analysis works, but how the analysis is accomplished. From the basic foundation laid in the introduction, chapters gradually increase in sophistication with particular emphasis on regression techniques (logistic, Poisson, conditional logistic, and log-linear) and then beyond to useful techniques that are not typically discussed in an applied context. Intuitive explanations richly supported with numerous examples produce an accessible presentation for readers interested in the analysis of data relevant to epidemiologic or medical research. Merging new material with updated, revised, and streamlined ideas from Dr. Selvin's highly successful Statistical Analysis of Epidemiologic Data, this text describes the analysis of epidemiologic and medical data that contributes to and supports a graduate student or researcher's "statistical tool box."

For more information about the book, and to download STATA outputs for the case studies presented in each chapter, please visit www.oup.com/us/statisticaltools.