Consider the random vector (X, Y), where Y represents a response variable and X an explanatory variable. The response Y is subject to random right censoring, whereas X is completely observed. Let m(x) be a conditional location function of Y given X = x. In this paper we assume that m(•) belongs to some parametric class M = {m θ : θ ∈ Θ} and we propose a new method for estimating the true unknown value θ 0. The method is based on nonparametric imputation for the censored observations. The consistency and asymptotic normality of the proposed estimator are established.