Introduction to Binary Logistic Regression

Abstract

Statistical inference with binary data presents many challenges, whether or not the observations are dependent or independent. Studies involving dependent observations tend to be longitudinal or clustered in nature, and therefore provide inefficient estimates if the correlation in the data is ignored. This chapter, then, reviews binary data under the assumption that the observations are independent. It provides an overview of the issues to be addressed in the book, as well as the different types of binary correlated data. It introduces SAS, SPSS, and R as the statistical programs used to analyze the data throughout the book and concludes with general recommendations.