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JSM 2012 Online Program

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CE_01C Sat, 7/28/2012, 8:30 AM - 5:00 PM HQ-Indigo A
Modeling Ordinal Categorical Data Part 1 (Two-Day Course) — Continuing Education Course
ASA
Instructor(s): Alan Agresti, University of Florida, Bernhard Klingenberg, Williams College
This short course surveys methods for analyzing categorical response variables that have a natural ordering of the categories. Such data often occur in the social sciences (e.g., for measuring attitudes and opinions) and in medical and public health disciplines (e.g., pain, quality of life, severity of a condition). Topics to be covered include ordinal odds ratios and association measures for contingency tables, logistic regression models using cumulative logits, other ordinal logistic regression models (adjacent-categories logits, continuation-ratio logits, partial proportional odds, non-proportional odds), other multinomial response models (cumulative probit, log-log), marginal models and random effects models for clustered ordinal responses and count data, and Bayesian approaches to ordinal model fitting. Examples in the course notes use R and SAS (PROC GENMOD, LOGISTIC, NLMIXED, FREQ), and references will be given for Stata and SPSS procedures. The presentation emphasizes interpretation of the methods rather than technical details, with examples including randomized clinical trials and social surveys such as the General Social Survey. Attendees are expected to have some familiarity with basic methods of categorical data analysis, including logistic regression models and chi-squared tests. The lectures will follow the book, `Analysis of Ordinal Categorical Data' by Alan Agresti (2nd ed., Wiley, 2010). Optional exercises will be given for a `practical session' the last couple of hours of the second day.



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