Xinguang C. Quantitative Epidemiology 2021

Textbook in PDF format

This book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers. It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges. Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention. Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data. In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poissonregression, Cox regression, missing data imputing, and statistical power analysis.
Front Matter
Introduction to Quantitative Epidemiology
Characters, Variables, Data, and Information
Quantitative Descriptive Epidemiology
Causal Exploration with Bivariate Analysis
Confirmation with Multiple Regression Analysis
Multiple Regression for Categorical and Counting Data
Survival Analysis and Cox Regression for Time-to-Event Data
Analysis of Two Influential Factors: Interaction and Mediation Modeling
Data Quantity, Missing Data, and Imputing
Sample Size, Statistical Power, and Power Analysis
Back Matter