title: Gini index estimation for lifetime data.
abstract: Lifetime data is often right-censored. Recent literature on the Gini index estimation with censored data focuses on independent censoring. However, the censoring mechanism is likely to be dependent censoring in practice. This paper proposes two estimators of the Gini index under independent censoring and covariate-dependent censoring, respectively. The proposed estimators are consistent and asymptotically normal. We also evaluate the performance of our estimators in finite samples through Monte Carlo simulations. Finally, the proposed methods are applied to real data.
authors.affiliation: School of International Business, Southwestern University of Finance and Economics, Chengdu, Sichuan, China. lvxiaofeng81@126.com.
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Lv
authors.affiliation: School of Public Policy and Management, University of Chinese Academy of Science, Beijing, 100049, China.|Institute of Policy and Management, Chinese Academy of Science, Beijing, 100190, China.
authors.forename: Gupeng
authors.initials: G
authors.lastname: Zhang
authors.affiliation: School of Economics, Capital University of Economics and Business, Beijing, China.
authors.forename: Guangyu
authors.initials: G
authors.lastname: Ren
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D015993:Life Tables; D009010:Monte Carlo Method
keywords: Covariate-dependent censoring; Gini index; Independent censoring; Lifetime data
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