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Estimation of the hazard function in a semiparametric model with covariate measurement error
2009
E S A I M: Probability & Statistics
We consider a failure hazard function, conditional on a time-independent covariate Z, given by η γ 0 (t)f β 0 (Z). The baseline hazard function η γ 0 and the relative risk f β 0 both belong to parametric families with θ 0 = (β 0 , γ 0 ) ∈ R m+p . The covariate Z has an unknown density and is measured with an error through an additive error model U = Z + ε where ε is a random variable, independent from Z, with known density fε. We observe a n-sample (Xi, Di, Ui), i = 1, . . . , n, where Xi is
doi:10.1051/ps:2008004
fatcat:nrtkb4cm6zcsnahapdzdn6m76i