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• W2045897497 abstract "A model for survival analysis is studied that is relevant for samples which are subject to multiple types of failure. In comparison with a more standard approach, through the appropriate use of hazard functions and transition probabilities, the model allows for a more accurate study of cause-specific failure with regard to both the timing and type of failure. A semiparametric specification of a mixture model is employed that is able to adjust for concomitant variables and allows for the assessment of their effects on the probabilities of eventual causes of failure through a generalized logistic model, and their effects on the corresponding conditional hazard functions by employing the Cox proportional hazards model. A carefully formulated estimation procedure is presented that uses an EM algorithm based on a profile likelihood construction. The methods discussed, which could also be used for reliability analysis, are applied to a prostate cancer data set." @default.
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• W2045897497 date "2008-01-07" @default.
• W2045897497 modified "2023-09-27" @default.
• W2045897497 title "Fitting a Semi-Parametric Mixture Model for Competing Risks in Survival Data" @default.
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• W2045897497 doi "https://doi.org/10.1080/03610920701649134" @default.
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