Description
This comprehensive resource explores regression models specifically designed for categorical and count data, offering both theoretical foundations and practical applications. The book covers essential techniques including logistic regression for binary outcomes, multinomial logistic regression for multiple categories, and Poisson and negative binomial regression for count data.
Readers will gain deep insights into model specification, estimation, interpretation, and diagnostics. The text includes real-world examples and case studies that demonstrate how to apply these models to practical problems across various disciplines including economics, epidemiology, social sciences, and business analytics.
The material progresses from foundational concepts to advanced topics, making it accessible to both beginners and experienced practitioners. Special attention is given to model selection, handling overdispersion, zero-inflated models, and dealing with common challenges in categorical and count data analysis.
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