Regression Analysis in R: A Comprehensive View for the Social Sciences covers the basic applications of multiple linear regression all the way through to more complex regression applications and extensions. Written for graduate level students of social science disciplines this book walks readers through bivariate correlation giving them a solid framework from which to expand into more complicated regression models. Concepts are demonstrated using R software and real data examples.

Key Features:

  • Full output examples complete with interpretation
  • Full syntax examples to help teach R code
  • Appendix explaining basic R functions
  • Methods for multilevel data that are often included in basic regression texts
  • End of Chapter Comprehension Exercises
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This book covers the basic applications of multiple linear regression all the way through to more complex regression applications and extensions. Written for graduate level students of social science disciplines this book walks readers through bivariate correlation.

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1. The Issue of Causality. 2. Describing Simple Relationships. 3. Linear Regression Analysis. 4. Regression Assumptions and Interpretational Considerations. 5. Dummy Variables and Interactions. 6. Hierarchical Regression. 7. Moderation and Mediation. 8. Dealing with Non- Linearity. 9. Regression Models for Nested Data. 10. Fixed Effects Modeling.
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Produktdetaljer

ISBN
9781032257754
Publisert
2022-07-27
Utgiver
Vendor
Chapman & Hall/CRC
Vekt
421 gr
Høyde
234 mm
Bredde
156 mm
Aldersnivå
U, G, 05, 01
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
180

Forfatter

Biografisk notat

Jocelyn E. Bolin is professor in the Department of Educational Psychology at Ball State University, where she teaches courses on introductory and intermediate statistics, multiple regression analysis, and multilevel modeling to graduate students in social science disciplines. She earned a PhD in educational psychology from Indiana University Bloomington. Her research interests include statistical methods for classification and clustering and use of multilevel modeling in the social sciences.