Regression Models for Categorical and Count Data

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Peter Martin - University College London, UK, Lecturer in Applied Statistics in the Department of Applied Health Research at University College London.

Additional resources:

Series:
The SAGE Quantitative Research Kit

Other Titles in:
Research Methods & Evaluation (General)

March 2022 | 272 pages | SAGE Publications Ltd

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

Introduction

Logistic regression

Ordinal logistic regression: the generalised ordered logit model

Multinomial logistic regression

Regression models for count data

The practice of modelling