The proportional odds cumulative incidence model for competing risks

Research output: Contribution to journalJournal articleResearchpeer-review

Frank Eriksson, Jianing Li, Thomas Scheike, Mei-Jie Zhang

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.

Original languageEnglish
Issue number3
Pages (from-to)687–695
Number of pages9
Publication statusPublished - Sep 2015

ID: 140626777