Additive hazards regression with current status data

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Abstract
Current status data arise when the only knowledge about the failure time of interest is whether the failure occurs before or after a random monitoring time. We propose to analyse such data by the semiparametric additive hazards model, which specifies that the hazard function for the failure time associated with a set of possibly time-dependent covariates is the sum of an arbitrary baseline hazard function and a regression function of covariates. Under certain conditions on the monitoring time, one can make inferences about the regression parameters of the additive hazards model by using the familiar asymptotic theory and software for the proportional hazards model with right censored data. An application to a carcinogenicity experiment is provided.

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