Regression for Health and Social Science: Applied Linear Models with R

This textbook provides a comprehensive introduction to linear model methods for students in the health and social sciences, with a focus on health issues. It assumes a pre-calculus background and covers topics such as linear regression, Poisson regression, logistic regression, survival analysis, and nonparametric regression. Examples are drawn from the news and current events, and R code is provided for easy application to students' own data.

Format: Hardback
Length: 294 pages
Publication date: 12 May 2022
Publisher: Cambridge University Press

This comprehensive textbook is designed for students studying health and social sciences, providing a foundational understanding of linear model methods with minimal mathematics prerequisites. It employs numerous real-world examples, particularly focusing on health-related issues, to facilitate a clear and accessible comprehension of the concepts. The book covers a range of methods, including linear regression models, Poisson regression, logistic regression, proportional hazards regression, survival analysis, and nonparametric regression. The author emphasizes the importance of interpreting computer output in relation to the motivating example, guiding readers in effectively applying the techniques to their own data. Extensive R code is provided, accompanied by detailed explanations, enabling readers to quickly apply these methods to their data. Additionally, numerous exercises and code examples are included to encourage critical thinking and deeper understanding of the analysis and its interpretation. The textbook's website, www.cambridge.org/zelterman, offers downloadable code and datasets for further exploration and application.

Weight: 678g
Dimension: 175 x 251 x 21 (mm)
ISBN-13: 9781108478182