Regression models for categorical and count data
Author(s)
Bibliographic Information
Regression models for categorical and count data
（The SAGE quantitative research kit / editors, Malcolm Williams, Richard D. Wiggins, D. Betsy McCoach）
SAGE, c2021
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Note
Includes bibliographical references (p. [237]-242) and index
Description and Table of Contents
Description
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
Table of Contents
Introduction
Logistic regression
Ordinal logistic regression: the generalised ordered logit model
Multinomial logistic regression
Regression models for count data
The practice of modelling
by "Nielsen BookData"