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> Regression for Health and Social Science

Regression for Health and Social Science

Applied Linear Models with R

Coming soon in April 2022


Daniel Zelterman, Yale University, Connecticut


This textbook for students in the health and social sciences covers the basics of linear model methods with a minimum of mathematics, assuming only a pre-calculus background. Numerous examples drawn from the news and current events with an emphasis on health issues, illustrate the concepts in an immediately accessible way. Methods covered include linear regression models, Poisson regression, logistic regression, proportional hazards regression, survival analysis, and nonparametric regression. The author emphasizes interpretation of computer output in terms of the motivating…

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Key features

  • Accessible, not mathematically demanding
  • Everyday examples allow students to understand the concepts without needing a lot of scientific context
  • R code is carefully explained, with an emphasis on interpreting the output

About the book