Daniel Zelterman (Connecticut Yale University)

Regression for Health and Social Science

Applied Linear Models with R

• Gebundenes Buch

Produktbeschreibung

Using every-day examples and numerous exercises, this text covers the basics of linear models with a minimum of mathematics. The emphasis is on issues involved in the analysis and the interpretation of computer output. R code is provided and explained allowing readers to apply the methods to their own data.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 294
• Erscheinungstermin: 12. Mai 2022
• Englisch
• Abmessung: 251mm x 177mm x 22mm
• Gewicht: 678g
• ISBN-13: 9781108478182
• ISBN-10: 1108478182
• Artikelnr.: 62814298

Autorenporträt

Daniel Zelterman, PhD, is Professor Emeritus, Department of Biostatistics, at Yale University. His application areas include work in clinical trial designs for cancer studies. Before moving to Yale in 1995, he was on the faculty of the University of Minnesota and at the State University of New York at Albany. He is an elected Fellow of the American Statistical Association. In his spare time he plays oboe and bassoon and has backpacked hundreds of miles of the Appalachian Trail.

Inhaltsangabe

Preface
Preface to revised edition
Acknowledgments
1. Introduction
2. Principles of statistics
3. Introduction to linear regression
4. Assessing the regression
5. Multiple linear regression
6. Indicators, interactions, and transformations
7. Nonparametric statistics
8. Logistic regression
9. Diagnostics for logistic regression
10. Poisson regression
11. Survival analysis
12. Proportional hazards regression
13. Review of methods
Appendix: statistical distributions
Selected solutions and hints
References
Index.