Generalized Linear Models for Bounded and Limited Quantitative Variables
eBook - ePub

Generalized Linear Models for Bounded and Limited Quantitative Variables

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

Generalized Linear Models for Bounded and Limited Quantitative Variables

About this book

This book introduces researchers and students to the concepts and generalized linear models for analyzing quantitative random variables that have one or more bounds. Examples of bounded variables include the percentage of a population eligible to vote (bounded from 0 to 100), or reaction time in milliseconds (bounded below by 0). The human sciences deal in many variables that are bounded. Ignoring bounds can result in misestimation and improper statistical inference. Michael Smithson and Yiyun Shou?s book brings together material on the analysis of limited and bounded variables that is scattered across the literature in several disciplines, and presents it in a style that is both more accessible and up-to-date. The authors provide worked examples in each chapter using real datasets from a variety of disciplines. The software used for the examples include R, SAS, and Stata. The data, software code, and detailed explanations of the example models are available on an accompanying website.

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Yes, you can access Generalized Linear Models for Bounded and Limited Quantitative Variables by Michael Smithson,Yiyun Shou in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Series
  4. Publisher Note
  5. Title Page
  6. Copyright Page
  7. CONTENTS
  8. Series
  9. Contributors
  10. Acknowledgements
  11. Chapter 1. Introduction and Overview
  12. Chapter 2. Models for Singly Bounded Variables
  13. Chapter 3. Models for Doubly Bounded Variables
  14. Chapter 4. Quantile Models for Bounded Variables
  15. Chapter 5. Censored and Truncated Variables
  16. CHAPTER 6. Extensions and Conclusions
  17. References
  18. Index