Development of Adaptive Step Function Regression for Survival Data

• Shimokawa Toshio

  University of Yamanashi

• Tsuji Mitsuhiro

  Kansai University

• Goto Masashi

  Biostatistical Research Association, NPO

Bibliographic Information

Other Title

• 生存時間研究における適応型ステップ関数回帰法の開発
• セイゾン ジカン ケンキュウ ニ オケル テキオウガタ ステップ カンスウ カイキホウ ノ カイハツ

Abstract

The prognostic factors affecting survival time are important components of survival analysis. Covariates may be evaluated by the tree-structured method, but this method has high-dimensional interaction. Tibshirani and LeBranc (1993) proposed an automatic binary logistic Estimator (ABLE) method for exploring such indices in binary outcomes. ABLE is constructed from linear combinations of index functions, and the regression parameters are estimated from maximum likelihood in a logistic regression model framework, namely, the automatic proportional hazard Estimator (APHE) model. In this paper, ABLE is extended to the right-censored survival response. The model incorporates the survival multivariate adaptive regression spline algorithm (LeBranc and Crowley, 1999). The effectiveness of the APHE method was validated on real data from phase III clinical trials for infectious diseases and via small-scale simulations.

Journal

• Ouyou toukeigaku

  Ouyou toukeigaku 43 (1-3), 23-43, 2014

  Japanese Society of Applied Statistics

Keywords

• classification and regression trees
• Cox proportional hazard model
• cancer research
• Automatic Binary Logistic Estimator

Details

• CRID: 1390001204442304000
• NII Article ID: 130005069596
• NII Book ID: AN00330942
• DOI: 10.5023/jappstat.43.23
• ISSN: 18838081
• ISSN: 02850370
• NDL BIB ID: 026026244
• Web Site: http://id.ndl.go.jp/bib/026026244
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I026026244
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed