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Categorical Data Analysis 3/e

作者：Alan Agresti
原價：NT$ 3,150

ISBN：9780470463635
版次：3
年份：2012
出版商：John Wiley
頁數/規格：714頁/精裝雙色

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Description
The use of statistical methods for analyzing categorical data has increased dramatically, particularly in the biomedical, social sciences, and financial industries. Responding to new developments, this book offers a comprehensive treatment of the most important methods for categorical data analysis.
Categorical Data Analysis, Third 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 loglinear models for discrete data with normal regression for continuous data. This edition also features:

An emphasis on logistic and probit regression methods for binary, ordinal, and nominal responses for independent observations and for clustered data with marginal models and random effects models

Two new chapters on alternative methods for binary response data, including smoothing and regularization methods, classification methods such as linear discriminant analysis and classification trees, and cluster analysis

New sections introducing the Bayesian approach for methods in that chapter

More than 100 analyses of data sets and over 600 exercises

Notes at the end of each chapter that provide references to recent research and topics not covered in the text, linked to a bibliography of more than 1,200 sources

A supplementary website showing how to use R and SAS; for all examples in the text, with information also about SPSS and Stata and with exercise solutions

Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and methodologists, such as biostatisticians and researchers in the social and behavioral sciences, medicine and public health, marketing, education, finance, biological and agricultural sciences, and industrial quality control.

Table of Contents
Preface
1 Introduction: Distributions and Inference for Categorical Data
2 Describing Contingency Tables
3 Inference for Two-Way Contingency Tables
4 Introduction to Generalized Linear Models
5 Logistic Regression
6 Building, Checking, and Applying Logistic Regression Models
7 Alternative Modeling of Binary Response Data
8 Models for Multinomial Responses
9 Loglinear Models for Contingency Tables
10 Building and Extending Loglinear Models
11 Models for Matched Pairs
12 Clustered Categorical Data: Marginal and Transitional Models
13 Clustered Categorical Data: Random Effects Models
14 Other Mixture Models for Discrete Data
15 Non-Model-Based Classification and Clustering
16 Large- and Small-Sample Theory for Multinomial Models
17 Historical Tour of Categorical Data Analysis
Appendix A Statistical Software for Categorical Data Analysis
Appendix B Chi-Squared Distribution Values
References
Author Index
Example Index
Subject Index
Appendix C Software Details for Text Examples (text website)
Appendix D Solutions to Selected Exercises (text website)

ALAN AGRESTI is Distinguished Professor Emeritus in the Department of Statistics at the University of Florida. He has presented short courses on categorical data methods in thirty countries. He is the author of five other books, including An Introduction to Categorical Data Analysis, Second Edition and Analysis of Ordinal Categorical Data, Second Edition, both published by Wiley.

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