Categorical Data Analysis

by Alan Agresti

Praise for the Second Edition"A must-have book for anyone expecting to do research and/or applications in categorical data analysis." -"Statistics in Medicine""It is a total delight reading this book." -"Pharmaceutical Research""If you do any analysis of categorical data, this is an essential desktop reference." -"Technometrics"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 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.

Genres: Mathematics, Science, Academic

752 pages, Kindle Edition

First published January 1, 1990

Reviews

[Oleksandr Nikitin · Rating 3 out of 5]

accidentally read a book :) chapter structure could be better, but if you have some experience structuring heaps of articles yourself - it would provide a nice overview of the field.

[Terran M · Rating 3 out of 5]

Comprehensive reference for methods in categorical data analysis. I found it was not a fun book to actually read large parts of; it felt like rapid-fire lists of techniques, with neither derivation nor narrative. Overall, I preferred reading Bilder and Loughlin, which covers less material but does a better job of what it covers.

[Goo · Rating 2 out of 5]

Textbook used for a course.

Okay as a collection of results, but not a great book to learn from.

[Jim Sullivan]

Very helpful; however, the reader will need a background in nonparametric statistics before pursuing this work or you may not get too much out of it.