Analysis of categorical data with R

By:

Bilder, Christopher R Loughin, Thomas M

Material type: Text

TextPublication details: New York CRC Press 2015Description: xiii, 533p. 26cm; Hard Includes bibliographical references and IndexISBN:

9781439855676

Subject(s):

Categories(Mathematics)-- Data processing R Computer Program Language R Computer programing language

DDC classification:

512.6 BIL

Contents:

Table of Contents Analyzing a Binary Response, Part 1: Introduction One binary variable Two binary variables Analyzing a Binary Response, Part 2: Regression Models Linear regression models Logistic regression models Generalized linear models Analyzing a Multicategory Response Multinomial probability distribution I x J contingency tables and inference procedures Nominal response regression models Ordinal response regression models Additional regression models Analyzing a Count Response Poisson model for count data Poisson regression models for count responses Poisson rate regression Zero inflation Model Selection and Evaluation Variable selection Tools to assess model fit Overdispersion Examples Additional Topics Binary responses and testing error Exact inference Categorical data analysis in complex survey designs "Choose all that apply" data Mixed models and estimating equations for correlated data Bayesian methods for categorical data Appendix A: An Introduction to R Appendix B: Likelihood Methods Bibliography Index

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	H.T. Parekh Library	GSB Collection	512.6 BIL (Browse shelf(Opens below))	Available		B1870

Alpha Books 1040/02Jan15/ Rs.5252/-

Table of Contents

Analyzing a Binary Response, Part 1: Introduction
One binary variable
Two binary variables

Analyzing a Binary Response, Part 2: Regression Models
Linear regression models
Logistic regression models
Generalized linear models

Analyzing a Multicategory Response
Multinomial probability distribution
I x J contingency tables and inference procedures
Nominal response regression models
Ordinal response regression models
Additional regression models

Analyzing a Count Response
Poisson model for count data
Poisson regression models for count responses
Poisson rate regression
Zero inflation

Model Selection and Evaluation
Variable selection
Tools to assess model fit
Overdispersion
Examples

Additional Topics
Binary responses and testing error
Exact inference
Categorical data analysis in complex survey designs
"Choose all that apply" data
Mixed models and estimating equations for correlated data
Bayesian methods for categorical data

Appendix A: An Introduction to R
Appendix B: Likelihood Methods

Bibliography

Index

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