Analysis of Categorical Data (ADDED FEE) — Professional Development Continuing Education Course
ASA , Biometrics Section
We live in a categorical world! From a positive or negative disease diagnosis to choosing all items that apply in a survey, outcomes are frequently organized into categories so that people can make sense of them. In this course, participants will learn how to analyze the most common types of categorical data. The course is divided into four main sections. The first three sections are organized by response type: 1) binary/binomial, 2) multicategory, and 3) count. Within each section, we examine how to estimate and interpret appropriate models while giving practical advice on their use. The fourth section applies model selection and evaluation methods to those models discussed in the first three. The ideal background for participants is experience with multiple linear regression and with the application of likelihood-based methods (e.g., likelihood ratio). All computations will be performed using R, so familiarity with its basics is recommended. Participants who will benefit the most are those who do not have experience with categorical methods and those who already have experience but have not used them in R. In addition to handouts and R programs to perform every computation, a recording of the course will be available to participants after JSM.
Instructor(s): Christopher Bilder, University of Nebraska-Lincoln, Thomas Loughin, Simon Fraser University
