SELECT * FROM sessions where years='2017' and sequence=118
December 4-8, 2017 at Atlantic City, New Jersey
The 73rd Deming Conference on Applied Statistics
Sponsored by Metropolitan Section, ASQ and Biopharmaceutical Section, ASA
   
abstract
      

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Generalized Linear Models

Speaker(s): Alan Agresti, Distinguished Professor Emeritus, University of Florida

Moderator: Wenjin Wang
 

This short course presents an overview of generalized linear modeling (GLM). After introducing basic results for GLMs, we present GLMs for four types of response variables: continuous responses, binary responses, multi-category responses, and count responses. Primary emphasis is on gamma regression for positive, skewed responses, logistic regression for binary response data, cumulative logit models for ordinal responses, and negative binomial regression for count responses. The presentation emphasizes interpretation rather than technical details. Examples primarily use R, with some examples also using SAS. The material covered is in Chapters 4-7 of the book "Foundations of Linear and Generalized Linear Models" (Wiley, 2015) by Alan Agresti



Alan Agresti is Distinguished Professor Emeritus of Statistics at the University of Florida. He is author or co-author of more than 100 articles and seven books, including "Categorical Data Analysis" (3rd ed. 2013), "Statistics: The Art and Science of Learning from Data"(4th ed. 2016), and "Foundations of Linear and Generalized Linear Models" (2015). He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics, Agresti has received an honorary doctorate from De Montfort University in the U.K., and the Statistician of the Year award from the Chicago chapter of the American Statistical Association.

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