Applications of Regression for Categorical Outcomes Using R
eBook - ePub

Applications of Regression for Categorical Outcomes Using R

  1. 222 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Applications of Regression for Categorical Outcomes Using R

About this book

This book covers the main models within the GLM (i.e., logistic, Poisson, negative binomial, ordinal, and multinomial). For each model, estimations, interpretations, model fit, diagnostics, and how to convey results graphically are provided. There is a focus on graphic displays of results as these are a core strength of using R for statistical analysis. Many in the social sciences are transitioning away from using Stata, SPSS and SAS, to using R, and this book uses statistical models which are relevant to the social sciences. Social Science Applications of Regression for Categorical Outcomes Using R will be useful for graduate students in the social sciences who are looking to expand their statistical knowledge, and for Quantitative social scientists due to it's ability to act as a practitioners guide.

Key Features:



  • Applied- in the sense that we will provide code that others can easily adapt


  • Flexible- R is basically just a fancy calculator. Our programs will enable users to derive quantities that they can use in their work


  • Timely- many in the social sciences are currently transitioning to R or are learning it now. Our book will be a useful resource


  • Versatile- we will write functions into an R package that can be applied to all of the regression models we will cover in the book


  • Aesthetically pleasing- one advantage of R relative to other software packages is that graphs are fully customizable. We will leverage this feature to yield high-end graphical displays of results


  • Affordability- R is free. R packages are free. There is no need to purchase site licenses or updates.

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Yes, you can access Applications of Regression for Categorical Outcomes Using R by David Melamed,Long Doan in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. List of Figures
  7. List of Tables
  8. Acknowledgments
  9. 1 Introduction
  10. 2 Introduction to R Studio and Packages
  11. 3 Overview of OLS Regression and Introduction to the Generalized Linear Model
  12. 4 Describing Categorical Variables and Some Useful Tests of Association
  13. 5 Regression for Binary Outcomes
  14. 6 Regression for Binary Outcomes – Moderation and Squared Terms
  15. 7 Regression for Ordinal Outcomes
  16. 8 Regression for Nominal Outcomes
  17. 9 Regression for Count Outcomes
  18. 10 Additional Outcome Types
  19. 11 Special Topics: Comparing between Models and Missing Data
  20. References
  21. Index