Tree-structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria
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The performance of computationally inexpensive model selection criteria in the context of tree-structured subgroup analysis is investigated. It is shown through simulation that no single model selection criterion exhibits a uniformly superior performance over a wide range of scenarios. Therefore, a two-stage approach for model selection is proposed and shown to perform satisfactorily. Applied example of subgroup analysis is presented. Problems associated with tree-structured subgroup analysis are discussed and practical solutions are suggested.
Keywordscensored survival data regression tree model selection two-stage approach subgroup analysis
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- Breiman L., Friedman J.H., Olshen R.A. and Stone C.J. 1984. Classification and Regression Trees. Wadsworth, Belmont, CA.Google Scholar
- Ciampi A., Lou Z., Lin Q. and Negassa A. 1991. Recursive partition and amalgamation with the exponential family: Theory and application. Applied Stochastic Models and Data Analysis 7: 121–137.Google Scholar
- Cox D.R. 1972. Regression models and life tables (with discussion). Journal of the Royal Statistical Society B 34: 187–220.Google Scholar
- Efron B. 1983. Estimating the error rate of a prediction rule: Improvement on cross-validation. Journal of the American Statistical Association 78: 316–331.Google Scholar
- Kalbfleisch J.D. and Prentice R.L. 1980. The Statistical Analysis of Failure Time Data. J. Wiley and Sons, New York.Google Scholar
- LeBlanc M. and Crowley J. 1993. Survival tree by goodness of split. Journal of the American Statistical Association 88: 457–467.Google Scholar
- Segal R.M. 1988. Regression tree for censored data. Biometrics 44: 35–47.Google Scholar
- Zhang H. and Singer B. 1999. Recursive Partitioning in the Health Sciences. Springer-Verlag, New York.Google Scholar