Applications of Regression Models in Epidemiology 1st Edition Erick Su?Rez

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Product details:

• ISBN-10 ‏ : ‎ 1119212480
• ISBN-13 ‏ : ‎ 978-1119212485
• Author:  Erick Suárez (Author), Cynthia M. Pérez (Author), Roberto Rivera (Author), Melissa N. Martínez (Author)

A one-stop guide for public health students and practitioners learning the applications of classical regression models in epidemiology

This book is written for public health professionals and students interested in applying regression models in the field of epidemiology. The academic material is usually covered in public health courses including (i) Applied Regression Analysis, (ii) Advanced Epidemiology, and (iii) Statistical Computing. The book is composed of 13 chapters, including an introduction chapter that covers basic concepts of statistics and probability. Among the topics covered are linear regression model, polynomial regression model, weighted least squares, methods for selecting the best regression equation, and generalized linear models and their applications to different epidemiological study designs. An example is provided in each chapter that applies the theoretical aspects presented in that chapter. In addition, exercises are included and the final chapter is devoted to the solutions of these academic exercises with answers in all of the major statistical software packages, including STATA, SAS, SPSS, and R. It is assumed that readers of this book have a basic course in biostatistics, epidemiology, and introductory calculus. The book will be of interest to anyone looking to understand the statistical fundamentals to support quantitative research in public health.

Table of contents:

Chapter 1: Basic Concepts for Statistical Modeling

Chapter 2: Introduction to Simple Linear Regression Models

Chapter 3: Matrix Representation of the Linear Regression Model

Chapter 4: Evaluation of Partial Tests of Hypotheses in a MLRM

Chapter 5: Selection of Variables in a Multiple Linear Regression Model

Chapter 6: Correlation Analysis

Chapter 7: Strategies for Assessing the Adequacy of the Linear Regression Model

Chapter 8: Weighted Least-Squares Linear Regression

Chapter 9: Generalized Linear Models

Chapter 10: Poisson Regression Models for Cohort Studies

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