AuthorEveritt, Brian. author
TitleAnalyzing Medical Data Using S-PLUS [electronic resource] / by Brian Everitt, Sophia Rabe-Hesketh
ImprintNew York, NY : Springer New York : Imprint: Springer, 2001
Connect tohttp://dx.doi.org/10.1007/978-1-4757-3285-6
Descript XII, 486 p. online resource

SUMMARY

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

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: Coxโs 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


SUBJECT

  1. Computer science
  2. Application software
  3. Biomathematics
  4. Statistics
  5. Computer Science
  6. Computer Applications
  7. Statistics for Life Sciences
  8. Medicine
  9. Health Sciences
  10. Statistics and Computing/Statistics Programs
  11. Physiological
  12. Cellular and Medical Topics