An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-step guide to using the free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, and substantial web-based support materials.
The Third Edition has been reorganized and includes a new chapter on mixed-effects models, new and updated data sets, and a de-emphasis on statistical programming, while retaining a general introduction to basic R programming. The authors have substantially updated both the car and effects packages for R for this edition, introducing additional capabilities and making the software more consistent and easier to use. They also advocate an everyday data-analysis workflow that encourages reproducible research. To this end, they provide coverage of RStudio, an interactive development environment for R that allows readers to organize and document their work in a simple and intuitive fashion, and then easily share their results with others. Also included is coverage of R Markdown, showing how to create documents that mix R commands with explanatory text.
Author(s): John Fox, Sanford Weisberg
Edition: 3rd
Publisher: SAGE
Year: 2019
Language: English
Commentary: PDF Convert
Pages: 802
Tags: Statistics, Regression Analysis, R
1. Getting Started with R and RStudio
2. Reading and Manipulating Data
3. Exploring and Transforming Data
4. Fitting Linear Models
5. Standard Errors, Confidence Intervals, Tests
6. Fitting Generalized Linear Models
7. Fitting Mixed-Effects Models
8. Regression Diagnostics
9. Drawing Graphs
10. An Introduction to R Programming