Description
Book SynopsisRegression 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
Table of Contents1. 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.
