Biostatistics Section Workshop 2016
Analysis of Categorical Data
Sunday, May 29, 2016 from 9 am to 4 pm, lunch included — Thistle 245
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 more easily make sense of them. In this workshop, participants will learn how to analyze the most common types of categorical data. The workshop 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. Focus will be on variable selection, evaluation of model fit, and solutions to overdispersion. The ideal background for participants is experience with multiple linear regression and with the application of likelihood-based methods (particularly Wald and likelihood-ratio methods).
This workshop is based on material from Chapters 1-5 of our Analysis of Categorical Data with Rtextbook, available from CRC Press. All computations will be performed using R. Familiarity with the basics of R, including object types and the use of functions, is recommended. In addition to handouts and R programs to perform every computation, a recording of the workshop will be available to participants after SSC.
Christopher R. Bilder is a Professor in the Department of Statistics at the University of Nebraska-Lincoln. Bilder has been the Principal Investigator for grants funded by the National Science Foundation and the National Institutes of Health involving research into categorical data analysis problems. His research has been published in a diverse set of outlets ranging from the Journal of the American Statistical Association to Chance. For his research involving a categorical data problem, Bilder was awarded the American Statistical Association's Outstanding Statistical Application Award in 2014. Since 2002, Bilder has taught a course on categorical data analysis to students majoring in statistics and to students majoring in a wide variety of other fields of study. He also has been a pioneer in using technology in and outside the classroom through his use of class video capturing, course websites, distance learning, hybrid (blended) learning, and tablets during his career.
Thomas M. Loughin is Professor and Chair of the Department of Statistics and Actuarial Science at Simon Fraser University. He is a professional, accredited Statistician (P.Stat. Statistical Society of Canada and American Statistical Association) with extensive experience in both statistical applications and methodological development. As a professor at Kansas State University and at Simon Fraser University, Loughin has worked with hundreds of researchers in a wide array of disciplines, including agriculture, engineering, medicine, education, and other areas. He specializes in communication with subject-matter experts and students, re-expressing complex statistical concepts into language that is easy to understand. Loughin also has years of experience teaching a categorical data analysis course to statistics and non-statistics majors. Loughin is a fellow of the American Statistical Association. He has held positions on the editorial boards of Biometrics, Technometrics, and Developmental Medicine and Child Neurology. His research has been funded by the National Science Foundation, the Natural Sciences and Engineering Research Council, and numerous other agencies.
Bilder and Loughin are authors of Analysis of Categorical Data with R, which was published in 2014 by CRC Press. They have constructed a website for the book that contains 77 R programs with over 11,000 lines of code. The website also provides 30 hours of instructional videos recorded while teaching a course on the analysis of categorical data.
Christopher R. Bilder, Ph.D.
University of Nebraska-Lincoln
Department of Statistics
340 Hardin Hall North, East Campus
Lincoln, NE 68583-0963
Phone: (402) 472-2903, Fax: (402) 472-5179
E-mail: firstname.lastname@example.org email@example.com
Thomas M. Loughin
Simon Fraser University
Department of Statistics & Actuarial Science
8888 University Drive
Burnaby, BC, Canada V5A 1S6
Phone: (778) 782-8037, Fax: (778) 782-4368