TY  - BOOK
AU  - Fox,John
TI  - Applied regression analysis and generalized linear models
SN  - 9781452205663
U1  - 000SA.06 23
PY  - 2016///
CY  - Los Angeles
PB  - SAGE
KW  - Regression analysis
KW  - Linear models (Statistics)
KW  - Social sciences
KW  - Statistical methods
N1  - Includes bibliographical references and indexes; 1. Statistical models and social science --
2. What is regression analysis? --
3. Examining data --
4. Transforming data --
5. Linear least-squares regression --
6. Statistical inference for regression --
7. Dummy-variable regression --
8. Analysis of variance --
9. Statistical theory for linear models --
10. The vector geometry of linear models --
11. Unusual and influential data --
12. Diagnosing non-normality, nonconstrant error variance, and nonlinearity --
13. Collinearity and its purported remedies --
14. Logit and probit models for categorical response variables --
15. Generalized linear models --
16. Time-series regression and generalized least squares --
17. Nonlinear regression --
18. Nonparametric regression --
19. Robust regression --
20. Missing data in regression models --
21. Bootstrapping regression models --
22. Model selection, averaging, and validation --
23. Linear mixed-effects models for hierarchical and longitudinal data --
24. Generalized linear and nonlinear mixed-effects models --
Appendices
N2  - Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the most useful and widely used statistical tools for social research.
ER  -