Title
Multivariate Survival Trees: A Maximum Likelihood Approach Based On Frailty Models
Keywords
Akaike information criterion; Frailty models; Multivariate survival times; Regression trees
Abstract
A method of constructing trees for correlated failure times is put forward. It adopts the backfitting idea of classification and regression trees (CART) (Breiman et al., 1984, in Classification and Regression Trees). The tree method is developed based on the maximized likelihoods associated with the gamma frailty model and standard likelihood-related techniques are incorporated. The proposed method is assessed through simulations conducted under a variety of model configurations and illustrated using the chronic granulomatous disease (CGD) study data.
Publication Date
3-1-2004
Publication Title
Biometrics
Volume
60
Issue
1
Number of Pages
93-99
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1111/j.0006-341X.2004.00139.x
Copyright Status
Unknown
Socpus ID
1642395595 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/1642395595
STARS Citation
Su, Xiaogang and Fan, Juanjuan, "Multivariate Survival Trees: A Maximum Likelihood Approach Based On Frailty Models" (2004). Scopus Export 2000s. 5268.
https://stars.library.ucf.edu/scopus2000/5268