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, Poisson regression, Cox regression, missing data
imputing, and statistical power analysis.