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The proportional odds cumulative incidence model for competing risks.

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.

SUBMITTER: Eriksson F

PROVIDER: S-EPMC4608382 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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The proportional odds cumulative incidence model for competing risks.

Eriksson Frank F Li Jianing J Scheike Thomas T Zhang Mei-Jie MJ

Biometrics 20150526 3

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 t ...[more]

PMID: 26013050

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