A kernel-assisted imputation estimating method for the additive hazards model with missing censoring indicator

In this paper, a nonparametric imputation method is developed for the additive hazards model when the censoring indicator is missing at random (MAR). The asymptotic properties of the proposed estimator are derived and the performance of the proposed estimator is demonstrated by a numerical simulation.

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Year of publication:	2015
Authors:	Qiu, Zhiping ; Chen, Xiaoping ; Zhou, Yong
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 98.2015, C, p. 89-97
Publisher:	Elsevier
Subject:	Additive hazards model \| Imputation \| Kernel smoothing \| Missing at random \| Missing data

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011189334