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Abstract:
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The generalized odds-rate model is a class of semiparametric regression models, which includes the proportional hazards and proportional odds models as special cases. There are few works on estimation of the generalized odds-rate models with interval censored data due to the challenges in maximizing the complex likelihood function. In this paper, we propose a gamma-Poisson data augmentation approach to develop an EM algorithm, which can be used to fit the generalized odds-rate model to interval censored data. The proposed EM algorithm is easy to implement and is computationally efficient. The performance of the proposed method is evaluated by comprehensive simulation studies and illustrated through applications to datasets from breast cancer and hemophilia studies. In order to make the proposed method easy to use in practice, an R package ``ICGOR" was developed.
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