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The proportional odds cumulative incidence model for competing risks. Biometrics 2015 Sep;71(3):687-95

Date

05/28/2015

Pubmed ID

26013050

Pubmed Central ID

PMC4608382

DOI

10.1111/biom.12330

Scopus ID

2-s2.0-84941733618 (requires institutional sign-in at Scopus site)   24 Citations

Abstract

We suggest an estimator for the proportional odds cumulative incidence model for competing risks data. The key advantage of this model is that the regression parameters have the simple and useful odds ratio interpretation. The model has been considered by many authors, but it is rarely used in practice due to the lack of reliable estimation procedures. We suggest such procedures and show that their performance improve considerably on existing methods. We also suggest a goodness-of-fit test for the proportional odds assumption. We derive the large sample properties and provide estimators of the asymptotic variance. The method is illustrated by an application in a bone marrow transplant study and the finite-sample properties are assessed by simulations.

Author List

Eriksson F, Li J, Scheike T, Zhang MJ

Author

Mei-Jie Zhang PhD Professor in the Institute for Health and Equity department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Bone Marrow Transplantation
Computer Simulation
Humans
Incidence
Myelodysplastic Syndromes
Odds Ratio
Proportional Hazards Models
Regression Analysis
Reproducibility of Results
Risk Assessment
Sensitivity and Specificity
Survival Analysis