Each chapter consists of basic statistical theory, simple examples of S-PLUS code, plus more complex examples of S-PLUS code, and exercises. All data sets are taken from genuine medical investigations and will be available on a web site. The examples in the book contain extensive graphical analysis to highlight one of the prime features of S-PLUS. Written with few details of S-PLUS and less technical descriptions, the book concentrates solely on medical data sets, demonstrating the flexibility of S-PLUS and its huge advantages, particularly for applied medical statisticians.

This book concentrates solely on medical data sets trying to demonstrate the flexibility of S-PLUS and its huge advantages, particularly for applied medical statisticians.

Written specifically for the medical field Uses S-PLUS to apply a variety of statistical methods Contains a mix of real data examples and background theory

Inhalt
Prologue.- 1 An Introduction to S-PLUS.- 2 Describing Data.- 3 Basic Inference.- 4 Scatterplots, Simple Regression and Smoothing.- 5 Analysis of Variance and Covariance.- 6 The Analysis of Longitudinal Data.- 7 More Graphics.- 8 Multiple Linear Regression.- 9 Generalized Linear Models I: Logistic Regression.- 10 Generalised linear models II: Poisson regression.- 11 Linear Mixed Models I.- 12 Linear Mixed Models II.- 13 Generalized Additive Models.- 14 Nonlinear models.- 15 Regression Trees.- 16 Survival Analysis I.- 17 Survival Analysis II: Cox's Regression.- 18 Principal Components and Factor Analysis.- 19 Cluster Analysis.- 20 Discriminant Function Analysis.- A The S-Plus Gui.- A.1 Introduction.- A.2 Statistical analysis using dialogue boxes.- A.3 Graphics using the GUI.- B Answers to selected exercises.- References.