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Analysis of categorical data with R Bilder, Christopher R.

By: Contributor(s): Material type: TextTextSeries: Texts in Statistical SciencePublication details: Boca Raton CRC Press 2015Description: xiii, 533 pISBN:
  • 9781439855676
Subject(s): DDC classification:
  • 512.6202855133 B4A6
Summary: Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice and guidelines on which procedures to use and why to use them. The Use of R as Both a Data Analysis Method and a Learning Tool requiring no prior experience with R, the text offers an introduction to the essential features and functions of R. It incorporates numerous examples from medicine, psychology, sports, ecology, and other areas, along with extensive R code and output. The authors use data simulation in R to help readers understand the underlying assumptions of a procedure and then to evaluate the procedure’s performance. They also present many graphical demonstrations of the features and properties of various analysis methods. (https://www.crcpress.com/Analysis-of-Categorical-Data-with-R/Bilder-Loughin/9781439855676)
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Item type Current library Collection Call number Status Date due Barcode Item holds
Book Book Ahmedabad Non-fiction 512.6202 855133 B4A6 (Browse shelf(Opens below)) Available 191145
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Table of Contents:

1. Analyzing a Binary Response, Part 1: Introduction

• One binary variable
• Two binary variables

2. Analyzing a Binary Response, Part 2: Regression Models

• Linear regression models
• Logistic regression models
• Generalized linear models

3. 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

4. Analyzing a Count Response

• Poisson model for count data
• Poisson regression models for count responses
• Poisson rate regression
• Zero inflation

5. Model Selection and Evaluation

• Variable selection
• Tools to assess model fit
• Overdispersion
• Examples

6. 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



Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice and guidelines on which procedures to use and why to use them.
The Use of R as Both a Data Analysis Method and a Learning Tool
requiring no prior experience with R, the text offers an introduction to the essential features and functions of R. It incorporates numerous examples from medicine, psychology, sports, ecology, and other areas, along with extensive R code and output. The authors use data simulation in R to help readers understand the underlying assumptions of a procedure and then to evaluate the procedure’s performance. They also present many graphical demonstrations of the features and properties of various analysis methods.

(https://www.crcpress.com/Analysis-of-Categorical-Data-with-R/Bilder-Loughin/9781439855676)

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