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Recursive partitioning in the health sciences /

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Bibliographic Details
Main Author: Zhang, Heping
Other Authors: Singer, Burton
Format: Book
Language:English
Published: New York : Springer, [1999]
Series:Statistics for biology and health.
Subjects:
Regression Analysis.
Analysis of Variance.
Statistics, Nonparametric.
Table of Contents:
  • Introduction
  • Examples using CART
  • The statistical problem
  • Outline of the methodology
  • A practical guide to tree construction
  • The elements of tree construction
  • Splitting a node
  • Terminal nodes
  • Download and use of software
  • Logistic regression
  • Logistic regression models
  • A logistic regression analysis
  • Classification trees for a binary response
  • Node impurity
  • Determination of terminal nodes
  • The standard error of Rcv*
  • Tree-based analysis of the Yale pregnancy outcome study
  • An alternative pruning approach
  • Localized cross-validation
  • Comparison between tree-based and logistic regression analyses
  • Missing data
  • Tree stability
  • Implementation
  • Risk-factor analysis using tree-based stratification
  • Background
  • The analysis
  • Analysis of censored data: examples
  • Tree-based analysis for the Western Collaborative Group Study data
  • Analysis of censored data: concepts and classical methods
  • The basics of survival analysis
  • Parametric regression for censored data
  • Analysis of censored data: survival trees
  • Splitting criteria
  • Pruning a survival tree
  • Implementation
  • Survival trees for the Western Collaborative Group Study data
  • Regression trees and adaptive splines for a continuous response
  • Tree representation of spline model and analysis of birth weight
  • Regression trees
  • The profile of MARS models
  • Modified MARS forward procedure
  • MARS backward-deletion step
  • The best knot
  • Restrictions on the knot
  • Smoothing adaptive splines
  • Numerical examples
  • Analysis of longitudinal data
  • Infant growth curves
  • The notation and a general model
  • Mixed-effects models
  • Semiparametric models
  • Adaptive spline models
  • Regression trees for longitudinal data
  • Analysis of multiple discrete responses
  • Parametric methods for binary responses
  • Classification trees for multiple binary responses
  • Application: analysis of BROCS data
  • Polytomous and longitudinal responses
  • Analysis of the BROCS data via log-linear models
  • Appendix
  • The script for running RTREE automatically
  • The script for running RTREE manually
  • The .inf file.