title: 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.
authors.affiliation: Section of Biostatistics, University of Copenhagen, Øster Farimagsgade 5, Copenhagen DK-1014, Denmark.
authors.forename: Frank
authors.initials: F
authors.lastname: Eriksson
authors.affiliation: Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, Wisconsin 53226, U.S.A.
authors.forename: Jianing
authors.initials: J
authors.lastname: Li
authors.affiliation: Section of Biostatistics, University of Copenhagen, Øster Farimagsgade 5, Copenhagen DK-1014, Denmark.
authors.forename: Thomas
authors.initials: T
authors.lastname: Scheike
authors.affiliation: Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, Wisconsin 53226, U.S.A.
authors.forename: Mei-Jie
authors.initials: MJ
authors.lastname: Zhang
mesh_terms: D016026:Bone Marrow Transplantation / Q000401:mortality*; D003198:Computer Simulation; D006801:Humans; D015994:Incidence; D009190:Myelodysplastic Syndromes / Q000401:mortality* / Q000628:therapy*; D016017:Odds Ratio; D016016:Proportional Hazards Models; D012044:Regression Analysis; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D012680:Sensitivity and Specificity; D016019:Survival Analysis
keywords: Competing risks; Estimating equations; Flexible modeling; Linear transformation model; Odds ratio; Proportional odds model; Semiparametric; Survival