A one-stop guide for public health students and practitioners learning the applications of classical regression models in epidemiology, “Applications of Regression Models in Epidemiology” is written by Erick Suárez. The book, published by Wiley on February 13, 2017, spans 13 chapters that cover a range of topics essential to understanding the statistical fundamentals necessary for quantitative research in public health.

Starting with an introduction chapter that revisits basic concepts of statistics and probability, the book delves into various regression models such as linear regression, polynomial regression, weighted least squares, and methods for selecting the best regression equation. It also explores generalized linear models and their applications to different epidemiological study designs.

In each chapter, an example is provided that applies the theoretical aspects discussed. To reinforce learning, exercises are included throughout the text, with solutions offered in the final chapter. These solutions cover major statistical software packages such as STATA, SAS, SPSS, and R, providing practical experience for readers.

Assuming a basic course in biostatistics, epidemiology, and introductory calculus, this book is designed to be accessible while offering depth to its subject matter. It will be of particular interest to public health professionals and students eager to understand the statistical tools used in their field.

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