Applied Regression Analysis and Generalized Linear Models
Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book.
Accompanying website resources: An instructor website for the book is available at edge.sagepub.com/fox3e containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the author′s website at: https://socialsciences.mcmaster.ca/jfox/Books/Applied-Regression-3E/index.html.
NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the author′s website: https://socialsciences.mcmaster.ca/jfox/Books/Applied-Regression-3E/bayes.html
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