Regression models for categorical and count data

著者

    • Martin, Peter

書誌事項

Regression models for categorical and count data

Peter Martin

(The SAGE quantitative research kit / editors, Malcolm Williams, Richard D. Wiggins, D. Betsy McCoach)

SAGE, c2021

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注記

Includes bibliographical references (p. [237]-242) and index

内容説明・目次

内容説明

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

目次

Introduction Logistic regression Ordinal logistic regression: the generalised ordered logit model Multinomial logistic regression Regression models for count data The practice of modelling

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