Regression trees and ensembles for cumulative incidence functions

Cho Youngjoo (), Molinaro Annette M. (), Hu Chen () and Strawderman Robert L. ()
Additional contact information
Cho Youngjoo: Department of Applied Statistics, Konkuk University, Seoul, Republic of Korea
Molinaro Annette M.: Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
Hu Chen: Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MA, USA
Strawderman Robert L.: Department of Biostatistics & Computational Biology, University of Rochester, Rochester, NY, USA

The International Journal of Biostatistics, 2022, vol. 18, issue 2, 397-419

Abstract: The use of cumulative incidence functions for characterizing the risk of one type of event in the presence of others has become increasingly popular over the past two decades. The problems of modeling, estimation and inference have been treated using parametric, nonparametric and semi-parametric methods. Efforts to develop suitable extensions of machine learning methods, such as regression trees and ensemble methods, have begun comparatively recently. In this paper, we propose a novel approach to estimating cumulative incidence curves in a competing risks setting using regression trees and associated ensemble estimators. The proposed methods use augmented estimators of the Brier score risk as the primary basis for building and pruning trees, and lead to methods that are easily implemented using existing R packages. Data from the Radiation Therapy Oncology Group (trial 9410) is used to illustrate these new methods.

Keywords: Brier score; CART; cause-specific hazard; competing risks; Fine and Gray model; random forests (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/ijb-2021-0014 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:ijbist:v:18:y:2022:i:2:p:397-419:n:13

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/ijb/html

DOI: 10.1515/ijb-2021-0014

Access Statistics for this article

The International Journal of Biostatistics is currently edited by Antoine Chambaz, Alan E. Hubbard and Mark J. van der Laan

More articles in The International Journal of Biostatistics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().