The proportional odds cumulative incidence model for competing risks

Biometrics. 2015 Sep;71(3):687-95. doi: 10.1111/biom.12330. Epub 2015 May 26.


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.

Keywords: Competing risks; Estimating equations; Flexible modeling; Linear transformation model; Odds ratio; Proportional odds model; Semiparametric; Survival.

MeSH terms

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