Regression Models for Categorical and Count Data

✍ Scribed by Peter Martin

Publisher: SAGE Publications
Year: 2022
Tongue: English
Leaves: 338
Series: The SAGE Quantitative Research Kit
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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

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

📜 SIMILAR VOLUMES

Regression Models for Categorical, Count

📁 Regression Models for Categorical, Count, and Related Variables-An applied approach

✍ John P. Hoffmann 📂 Library 📅 2016 🏛 University of California Press 🌐 English

Regression Models for Categorical, Count

📁 Regression Models for Categorical, Count, and Related Variables: An Applied Approach

✍ John P. Hoffmann 📂 Library 📅 2016 🏛 University of California Press 🌐 English

<p>Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists co

Discrete Data Analysis with R Visualizat

📁 Discrete Data Analysis with R Visualization and Modeling Techniques for Categorical and Count Data

✍ Michael Friendly, David Meyer 📂 Library 📅 2015 🌐 English

A early publishing of CRC Press. No the final one.

Discrete Data Analysis with R : Visualiz

📁 Discrete Data Analysis with R : Visualization and Modeling Techniques for Categorical and Count Data.

✍ Friendly, Michael; Meyer, David 📂 Library 📅 2015 🏛 Chapman and Hall/CRC 🌐 English

An Applied Treatment of Modern Graphical Methods for Analyzing Categorical Data Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and

Regression Models for Count Data in R +

📁 Regression Models for Count Data in R + Code

✍ Zeileis A., Kleiber C., Jackman S. 📂 Library 🌐 English

The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of th

Regression for Categorical Data

📁 Regression for Categorical Data

✍ Gerhard Tutz, Ludwig-Maximilians-Universität Munchen 📂 Library 📅 2012 🏛 Cambridge University Press 🌐 English