Regression Models for Categorical and Count Data

Regression Models for Categorical and Count Data by Peter Martin, published by Sage on March 7, 2022, is a comprehensive guide designed for those looking to conduct regression analysis on categorical and count data. This 272-page text provides practical guidance, combining theoretical foundations with real-world applications, and is presented in English. The book includes numerous graphs to support the learning process, making it accessible for researchers in various fields.

Readers will find detailed instructions on using logistic regression models for binary, ordinal, and multinomial outcomes, as well as insights into applying count regression techniques such as Poisson and negative binomial models. The text emphasizes the importance of selecting the most suitable model for specific research needs and outlines general principles of effective statistical modeling. As part of The SAGE Quantitative Research Kit, this edition equips readers with the necessary skills and confidence to navigate their quantitative research endeavors.