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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.
Content Level »Research
Keywords »Analysis of medical Data - Boxplot - Factor analysis - Fitting - Generalized linear model - Medical Data - S-PLUS - Statistical Methods - Survival analysis - Time series - analysis of variance - cluster analysis - correlation - linear regression - statistics
An Introduction to S-PLUS * Describing Data * Basic Inference * Scatterplots, Simple Regression and Smoothing * Analysis of Variance and Covariance * The Analysis of Longitudinal Data * More Graphics * Multiple Linear Regression * Generalized Linear Models I: Logistic Regression * Generalized Linear Models II: Poisson Regression * Linear Mixed Models I * Linear Mixed Models II * Generalized Additive Models * Nonlinear models * Regression Trees · Survival Analysis I · Survival Analysis II: Cox's Regression * Principal Components and Factor Analysis * Cluster Analysis * Discriminant Function Analysis * The S-PLUS GUI