Additive time-dependent hazard model with doubly truncated data

被引：14

作者：

Frank, Gordon ^{[1
]}

Chae, Minwoo ^{[2
]}

Kim, Yongdai ^{[3
]}

机构：

[1] Univ Rostock, Fac Econ & Social Sci, Rostock, Germany

[2] Case Western Reserve Univ, Dept Math Appl Math & Stat, Cleveland, OH 44106 USA

[3] Seoul Natl Univ, Dept Stat, Seoul, South Korea

来源：

JOURNAL OF THE KOREAN STATISTICAL SOCIETY | 2019年 / 48卷 / 02期

关键词：

Additive hazard model; Insolvency risk; Non-parametric; Random double-truncation; Time-dependent regression coefficients; LINEAR-REGRESSION MODEL; PROPORTIONAL-HAZARDS; SEMIPARAMETRIC ANALYSIS; SURVIVAL; FAILURE; INDEPENDENCE; ESTIMATOR;

D O I：

10.1016/j.jkss.2018.10.005

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

For doubly truncated data, i.e. the variables of interest are only observable if they lie in a certain random interval, an additive hazard model with time-dependent regression coefficients is investigated. Consistency and asymptotic normality are proven under mild assumptions. A simulation study investigates the finite sample properties and the influence of the truncation distribution on the estimation error. Finally, the method is applied to a doubly truncated data set of German companies, where the age at insolvency is of interest. (C) 2018 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.

引用

页码：179 / 193

页数：15

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