Modern Regression Techniques Using R
A Practical Guide
- Daniel B Wright - University of Nevada, Las Vegas, USA
- Kamala London - University of Toledo, USA
Mathematics & Statistics | Regression & Correlation
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 out using a range of real research examples conducted by the authors in every chapter.
Given the wide coverage of techniques, this book will be essential reading for any advanced undergraduate and graduate student (particularly in psychology) and for more experienced researchers wanting to learn how to apply some of the more recent statistical techniques to their datasets.
The Authors are donating all royalties from the book to the American Partnership for Eosinophilic Disorders.
`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 University
Nice compact format. Recommended only for advanced courses in econometrics as some topics are presented but not explained (e.g. diagnostic plots in chapter "Basic regression".
The book is an invaluable resource for those students wanting to learn more about R and advanced statistics techniques.
In our University, at the Department of Sociology we have recently started to shift our statistics classes from SPSS-centric to R-philosophy. In this respect, R-based books that treat commonly used techniques like regression are most welcomed resources, as it is not only the students' training that we need to change, but most frequently our colleagues' misperceptions due to practice over the years.
It seems like a very good text for an introductory course, and I am going to recommend that students use it as a supplemental test and see how well they do.
I pushed for using R in the course, but was not allowed to make change (we are sticking with Excel as data analysis tool.)
Good book with great examples!
Sample Materials & Chapters
Data and Code for Modern Regression Techniques
Changes in R that affect the code in this book