Modern Regression Techniques Using R A Practical Guide [Paperback]

In a way that is refreshingly engaging and readable, Daniel B. Wright and Kamala London describe the most useful of these techniques and provide step-by-step instructions, using the freeware R, to analyze datasets that can be located on the books' webpage via the SAGE homepage. Techniques covered in this book include multilevel modeling, ANOVA and ANCOVA, path analysis, mediation and moderation, logistic regression (generalized linear models), generalized additive models, and robust methods. These are all tested using a range of real research examples conducted by the authors in every chapter.
In a way that is refreshingly engaging and readable, Daniel B. Wright and Kamala London describe the most useful of these techniques and provide step-by-step instructions, using the freeware R, to analyze datasets that can be located on the books' webpage via the SAGE homepage. Techniques covered in this book include multilevel modeling, ANOVA and ANCOVA, path analysis, mediation and moderation, logistic regression (generalized linear models), generalized additive models, and robust methods. These are all tested using a range of real research examples conducted by the authors in every chapter.
`An impressive resource for lecturers and researchers in a relatively slim text. I particularly like the way it rapidly builds on basic regression models to introduce genuinely advanced and cutting edge techniques. It is also very useful that the examples are implemented in the free, cross-platform statistical software environment R' - Dr Thom Baguley, Psychology, Nottingham Trent UniversityVery Brief Introduction to R
Very brief introduction to R
The basic regression
ANOVA as regression
ANCOVA: Lord's paradox and mediation analysis
Model selection and shrinkage
Generalized linear models (GLMs)
Regression splines and generalized additive models (GAMs)
MultilelC‘