Categorical Data Analysis

Catalog description

Categorical data are often encountered in many disciplines including the fields of clinical and biological sciences. Analysis methods for categorical data are different from the analysis methods for continuous data. There is a rich collection of methods for categorical data analysis. The elegant "odds ratio" interpretation associated with categorical data is a unique one. This online course will cover cross-sectional categorical data analysis theories and methods. From this course, students will learn standard categorical data analysis methods and its applications to biomedical and clinical studies. This course will focus mostly on statistical methods for categorical data analysis arising from various fields of study including clinical studies. The course will include recorded-video lectures, quizzes, homeworks, simulations, and data analysis on real and realistic problems in human health tied directly to the student's own professional interests. The focus will be given to logistic regression methods. Topics may include (but are not limited to) binary response, multicategory response, count response, model selection, and evaluation, and exact inference methods for categorical data. This course stresses how the core statistical principles, computing tools, and visualization strategies are used to address complex scientific aims powerfully and efficiently, and to communicate those findings effectively to researchers who may have little or no experience in these methods. Prereq: PQHS 431 .