Analyzing categorical data

Autori

• Jeffrey S. Simonoff

Parametri

• 496 pagine
• 18 ore di lettura

• Matematica

Maggiori informazioni sul libro

Categorical data frequently appear across various fields such as biometrics, economics, management, and sociology. This book introduces the analysis of such data, primarily utilizing loglinear Poisson regression and logistic binomial regression models. It covers a wide array of topics, including count regression models like Poisson, negative binomial, and zero-inflated models; loglinear models for contingency tables; and regression models for binary and multiple-category target variables. The methods are illustrated with real data analyses from recent journal articles, providing detailed context, model checking, and scientific implications. Over 200 exercises are included, many based on current literature, with data sets and computer code available online. The text has received positive feedback for its practical approach and extensive examples, making it suitable for readers with varying statistical backgrounds. It emphasizes the connection between statistical methods and regression modeling, offering insights into both common and less frequently covered topics. Overall, the book serves as a comprehensive resource for researchers and practitioners dealing with categorical data, providing clear methodologies and practical guidelines for analysis.

Lingua: Inglese

Pubblicato: 2003