Statistical Tools for Epidemiologic Research

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Product Description

In this innovative new book, Steve Selvin provides readers with a clear understanding of intermediate biostatistical methods without advanced mathematics or statistical theory (for example, no Bayesian statistics, no causal inference, no linear algebra and only a slight hint of calculus). 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.

Statistical Tools for Epidemiologic Research Review

I took a course at the Johns Hopkins Bloomberg School of Public Health which recommended this book for the course. Thankfully, I got the Kindle version of the book and was able to follow along with the instructor who was madly writing extreme math formulas on a blackboard. The book is very heavy, and unless you are into logistic regression and other advanced stats, this book will be way too complex to understand.

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