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Introduction to Categorical Data Analysis

Alan Agresti
€136.99
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Bayesian Inference
Binary Regression Models
Bradley-Terry Model
Categorical Data
Categorical Response Data
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Category=UNC
Chi-Squared Tests of Independence
Cluster Analysis for Categorical Responses
Conditional Likelihood
Contingency Tables
Count Response Variables
Discrete Data
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Exact Frequentist
Generalized Additive Models
Generalized Linear Mixed Models
Generalized Linear Models
Latent Class Models
Linear Discriminant Analysis
Linear Probability
Link Models
Logistic Regression
Logit Models
Loglinear Models
Marginal Models
Matched Pairs
Model Checking
Model Selection
Multilevel Models
Multinomial Responses
Nominal Matched-Pairs Responses
Odds Ratio
Ordinal Variables
Penalized Likelihood
Probability Distributions
Probability Structure
Probit Models
R Software
Random Effects Modeling
Rater Agreement
ROC Curves
Statistical
Statistical Inference
Tree-Based Prediction

Product details

  • ISBN 9781119405269
  • Weight: 703g
  • Dimensions: 183 x 257mm
  • Publication Date: 22 Jan 2019
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description

A valuable new edition of a standard reference

The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data.

Adding to the value in the new edition is:

• Illustrations of the use of R software to perform all the analyses in the book

• A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis

• New sections in many chapters introducing the Bayesian approach for the methods of that chapter

• More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets

• An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises

Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more.

An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.
About Alan Agresti

ALAN AGRESTI is Distinguished Professor Emeritus at the University of Florida. He has presented short courses on categorical data methods in 35 countries. He is the author of seven books, including the bestselling Categorical Data Analysis (Wiley), Foundations of Linear and Generalized Linear Models (Wiley), Statistics: The Art and Science of Learning from Data (Pearson), and Statistical Methods for the Social Sciences (Pearson).

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