Analyzing Medical Data Using S-PLUS [Hardcover]

Each chapter will consist of basic statistical theory, simple examples of S-PLUS code, more complex examples of S-PLUS code, and exercises. All data sets will be taken from genuine medical investigations and will be made available, if possible, on a web site. All examples will contain extensive graphical analysis to highlight one of the prime features of S-PLUS. The book would complement Venables and Ripley (VR). However, there is far less about the details of S-PLUS and probably less technical descriptions of techniques. The book concentrates solely on medical data sets trying to demonstrate the flexibility of S-PLUS and its huge advantages, particularly for applied medical statisticians.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: Coxs 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.

From the reviews:

TECHNOMETRICS

&a well-organized, nicely conceived book that will be useful to practitioners with S-PLUS in any environment.

SHORT BOOK REVIEWS

This book presents a survey of modern methods used in, but not confined to, medical statistics, each accompanied by a brief summary of the mathematical components, instruction in the basics of the S-PLUS computer language, up-tlc/