Regression Models for Categorical and Count Data (Paperback)


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

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Product 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

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Product Details

General

Imprint

Sage Publications Ltd

Country of origin

United Kingdom

Series

The SAGE Quantitative Research Kit

Release date

March 2022

Availability

Expected to ship within 12 - 17 working days

First published

2022

Authors

Dimensions

242 x 170 x 18mm (L x W x T)

Format

Paperback

Pages

272

ISBN-13

978-1-5297-6126-9

Barcode

9781529761269

Categories

LSN

1-5297-6126-3



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