The Statistical Analysis of Discrete Data

1. Front Matter

   Pages i-xii

   PDF

2. Introduction

   • Thomas J. Santner, Diane E. Duffy

   Pages 1-20

3. Univariate Discrete Responses

   • Thomas J. Santner, Diane E. Duffy

   Pages 21-112

4. Loglinear Models

   • Thomas J. Santner, Diane E. Duffy

   Pages 113-141

5. Cross-Classified Data

   • Thomas J. Santner, Diane E. Duffy

   Pages 142-203

6. Univariate Discrete Data with Covariates

   • Thomas J. Santner, Diane E. Duffy

   Pages 204-286

7. Back Matter

   Pages 287-372

   PDF

The Statistical Analysis of Discrete Data provides an introduction to cur­ rent statistical methods for analyzing discrete response data. The book can be used as a course text for graduate students and as a reference for researchers who analyze discrete data. The book's mathematical prereq­ uisites are linear algebra and elementary advanced calculus. It assumes a basic statistics course which includes some decision theory, and knowledge of classical linear model theory for continuous response data. Problems are provided at the end of each chapter to give the reader an opportunity to ap­ ply the methods in the text, to explore extensions of the material covered, and to analyze data with discrete responses. In the text examples, and in the problems, we have sought to include interesting data sets from a wide variety of fields including political science, medicine, nuclear engineering, sociology, ecology, cancer research, library science, and biology. Although there are several texts available on discrete data analysis, we felt there was a need for a book which incorporated some of the myriad recent research advances. Our motivation was to introduce the subject by emphasizing its ties to the well-known theories of linear models, experi­ mental design, and regression diagnostics, as well as to describe alterna­ tive methodologies (Bayesian, smoothing, etc. ); the latter are based on the premise that external information is available. These overriding goals, to­ gether with our own experiences and biases, have governed our choice of topics.

• Logistic Regression
• calculus
• linear algebra
• statistical analysis
• statistics

"The book incorporates a good selection from the broad range of recent research advances... The text shows both the practical experience and the theoretical knowledge of the authors."
(Computational Statistics)

• School of Operations Research and Industrial Engineering, Cornell University, Ithaca, USA

  Thomas J. Santner

• Bell Communications Research, Morristown, USA

  Diane E. Duffy

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