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The proportional odds cumulative incidence model for competing risks
Author(s) -
Eriksson Frank,
Li Jianing,
Scheike Thomas,
Zhang MeiJie
Publication year - 2015
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12330
Subject(s) - odds , estimator , statistics , cumulative incidence , goodness of fit , odds ratio , variance (accounting) , incidence (geometry) , mathematics , econometrics , sample (material) , confidence interval , computer science , logistic regression , economics , cohort , accounting , geometry , chemistry , chromatography
Summary 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.