Regression Models for Categorical and Count Data

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This text provides practical guidance on conducting regression analysis on categorical and count data. Step by step and supported by lots of helpful graphs, it covers both the theoretical underpinnings of these methods as well as their application, giving you the skills needed to apply them to your own research. It offers guidance on:

  • Using logistic regression models for binary, ordinal, and multinomial outcomes
  • Applying count regression, including Poisson, negative binomial, and zero-inflated models
  • Choosing the most appropriate model to use for your research
  • The general principles of good statistical modelling in practice.

Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey

Author(s): Peter Martin
Series: The SAGE Quantitative Research Kit
Publisher: SAGE Publications
Year: 2022

Language: English
Pages: 337
City: Los Angeles

Half Title
Acknowledgements
Title Page
Copyright Page
Contents
Illustration List
About the Author
Acknowledgements
Preface
1 Introduction
2 Logistic Regression
3 Ordinal Logistic Regression: The Generalised Ordered Logit Model
4 Multinomial Logistic Regression
5 Regression Models for Count Data
6 The Practice of Modelling
Glossary
References
Index