Amstat News asked three review editors to rate their top
five favorite books in the September 2003 issue. Categorical
Data Analysis was among those chosen.
A valuable new edition of a standard reference
"A 'must-have' book for anyone expecting to do research and/or
applications in categorical data analysis."
-Statistics in Medicine on Categorical Data Analysis,
First Edition
The use of statistical methods for categorical data has
increased dramatically, particularly for applications in the
biomedical and social sciences. Responding to new developments in
the field as well as to the needs of a new generation of
professionals and students, this new edition of the classic
Categorical Data Analysis offers a comprehensive
introduction to the most important methods for categorical data
analysis.
Designed for statisticians and biostatisticians as well as
scientists and graduate students practicing statistics,
Categorical Data Analysis, Second Edition summarizes the
latest methods for univariate and correlated multivariate
categorical responses. Readers will find a unified generalized
linear models approach that connects logistic regression and
Poisson and negative binomial regression for discrete data with
normal regression for continuous data. Adding to the value in the
new edition is coverage of:
* Three new chapters on methods for repeated measurement and
other forms of clustered categorical data, including marginal
models and associated generalized estimating equations (GEE)
methods, and mixed models with random effects
* Stronger emphasis on logistic regression modeling of binary
and multicategory data
* An appendix showing the use of SAS for conducting nearly all
analyses in the book
* Prescriptions for how ordinal variables should be treated
differently than nominal variables
* Discussion of exact small-sample procedures
* More than 100 analyses of real data sets to illustrate
application of the methods, and more than 600 exercises
* An Instructor's Manual presenting detailed solutions to all
the problems in the book is available from the Wiley editorial
department.
Autorentext
ALAN AGRESTI, PhD, is Distinguished Professor in the Department of Statistics at the University of Florida. He has published extensively on categorical data methods and has presented courses on the topic for universities, companies, and professional organizations worldwide. A Fellow of the American Statistical Association, he is also the author of two other Wiley texts on categorical data analysis and coauthor of Statistical Methods for the Social Sciences.
Klappentext
A valuable new edition of a standard reference
"A 'must-have' book for anyone expecting to do research and/or applications in categorical data analysis."
Statistics in Medicine on Categorical Data Analysis, First Edition
The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. Responding to new developments in the field as well as to the needs of a new generation of professionals and students, this new edition of the classic Categorical Data Analysis offers a comprehensive introduction to the most important methods for categorical data analysis.
Designed for statisticians and biostatisticians as well as scientists and graduate students practicing statistics, Categorical Data Analysis, Second Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial regression for discrete data with normal regression for continuous data. Adding to the value in the new edition is coverage of:
- Three new chapters on methods for repeated measurement and other forms of clustered categorical data, including marginal models and associated generalized estimating equations (GEE) methods, and mixed models with random effects
- Stronger emphasis on logistic regression modeling of binary and multicategory data
- An appendix showing the use of SAS for conducting nearly all analyses in the book
- Prescriptions for how ordinal variables should be treated differently than nominal variables
- Discussion of exact small-sample procedures
- More than 100 analyses of real data sets to illustrate application of the methods, and more than 600 exercises
Zusammenfassung
Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Categorical Data Analysis was among those chosen.
A valuable new edition of a standard reference
"A 'must-have' book for anyone expecting to do research and/or applications in categorical data analysis."
Statistics in Medicine on Categorical Data Analysis, First Edition
The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. Responding to new developments in the field as well as to the needs of a new generation of professionals and students, this new edition of the classic Categorical Data Analysis offers a comprehensive introduction to the most important methods for categorical data analysis.
Designed for statisticians and biostatisticians as well as scientists and graduate students practicing statistics, Categorical Data Analysis, Second Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial regression for discrete data with normal regression for continuous data. Adding to the value in the new edition is coverage of:
- Three new chapters on methods for repeated measurement and other forms of clustered categorical data, including marginal models and associated generalized estimating equations (GEE) methods, and mixed models with random effects
- Stronger emphasis on logistic regression modeling of binary and multicategory data
- An appendix showing the use of SAS for conducting nearly all analyses in the book
- Prescriptions for how ordinal variables should be treated differently than nominal variables
- Discussion of exact small-sample procedures
- More than 100 analyses of real data sets to illustrate application of the methods, and more than 600 exercises
- An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Inhalt
Preface xiii
1. Introduction: Distributions and Inference for Categorical Data 1
2. Describing Contingency Tables 36
3. Inference for Contingency Tables 70
4. Introduction to Generalized Linear Models 115
5. Logistic Regression 165
6. Building and Applying Logistic Regression Models 211
7. Logit Models for Multinomial Responses 267
8. Loglinear Models for Contingency Tables 314
9. Building and Extending Loglinear/Logit Models 357
10. Models for Matched Pairs 409
11. Analyzing Repeated Categorical Response Data 455
12. Random Effects: Generalized Linear Mixed Models for Categorical Responses 491
13. Other Mixture Models for Categorical Data* 538
14. Asymptotic Theory for Parametric Models 576
15. Alternative Estimation Theory for Parametric Models 600
16. Hi…