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Categorical Data Analysis, 3e (Hardcover, 3rd Edition)
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Categorical Data Analysis, 3e (Hardcover, 3rd Edition)
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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 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.
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