Categorical Data Analysis
Aus der Reihe
Wiley Series in Probability and Statistics
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Form:Einzelkauf Download
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Sprache:Englisch
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eBook Format:PDF
- PDF 114,99 € ausgewählt
- ePUB 143,99 €
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Verlag:John Wiley & Sons
- John Wiley & Sons 114,99 € ausgewählt
- For Dummies 143,99 €
114,99 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
31.03.2003
Verlag
John Wiley & SonsSeitenzahl
734 (Printausgabe)
Dateigröße
4159 KB
Auflage
2. Auflage
Sprache
Englisch
EAN
9780471458760
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.
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.
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