Shows how to obtain informative graphical output using R
Provides R code so readers can perform their own analyses
Emphasizes the practical application and interpretation of results rather than focusing on the theory behind the analyses
Offers an introduction to R, including a summary of its most important features
Contains many examples and exercises


An Introduction to R
What Is R?
Installing R
Help and Documentation
Data Objects in R
Data Import and Export
Basic Data Manipulation
Computing with Data
Organizing an Analysis
Data Analysis Using Graphical Displays
Introduction
Initial Data Analysis
Analysis Using R
Simple Inference
Introduction
Statistical Tests
Analysis Using R
Conditional Inference
Introduction
Conditional Test Procedures
Analysis Using R
Analysis of Variance
Introduction
Analysis of Variance
Analysis Using R
Simple and Multiple Linear Regression
Introduction
Simple Linear Regression
Multiple Linear Regression
Analysis Using R
Logistic Regression and Generalized Linear Models
Introduction
Logistic Regression and Generalized Linear Models
Analysis Using R
Density Estimation
Introduction
Density Estimation
Analysis Using R
Recursive Partitioning
Introduction
Recursive Partitioning
Analysis Using R
Scatterplot Smoothers and Generalized Additive Models
Introduction
Scatterplot Smoothers and Generalized Additive Models
Analysis Using R
Survival Analysis
Introduction
Survival Analysis
Analysis Using R
Analyzing Longitudinal Data I
Introduction
Analyzing Longitudinal Data
Linear Mixed Effects Models
Analysis Using R
Prediction of Random Effects
The Problem of Dropouts
Analyzing Longitudinal Data II
Introduction
Methods for Nonnormal Distributions
Analysis Using R: GEE
Analysis Using R: Random Effects
Simultaneous Inference and Multiple Comparisons
Introduction
Simultaneous Inference and Multiple Comparisons
Analysis Using R
Meta-Analysis
Introduction
Systematic Reviews and Meta-Analysis
Statistics of Meta-Analysis
Analysis Using R
Meta-Regression
Publication Bias
Principal Component Analysis
Introduction
Principal Component Analysis
Analysis Using R
Multidimensional Scaling
Introduction
Multidimensional Scaling
Analysis Using R
Cluster Analysis
Introduction
Cluster Analysis
Analysis Using R
Bibliography
Index
A Summary appears at the end of each chapter