Semiparametric analysis of competing risks data with covariate measurement error

被引：1

作者：

Jayanagasri, Akurathi ^{[1
]}

Anjana, S. ^{[1
]}

机构：

[1] Univ Hyderabad, Sch Math & Stat, Hyderabad 500046, Telangana, India

来源：

COMPUTATIONAL STATISTICS | 2025年 / 40卷 / 02期

关键词：

Competing risks; Estimating equations; Linear transformation model; SIMEX; LINEAR TRANSFORMATION MODELS; PROPORTIONAL HAZARDS MODEL; CUMULATIVE INCIDENCE; EFFICIENT ESTIMATION; REGRESSION;

D O I：

10.1007/s00180-024-01502-4

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：

This paper deals with the competing risks data with covariate measurement error. A semiparametric linear transformation model for the right-censored competing risks data when the covariates are measured with error is proposed. The parameters involved in the model are estimated using a set of estimating equations. An adaptable simulation extrapolation (SIMEX) technique is employed to handle the covariate measurement error. Simulation studies are conducted, to examine the finite sample properties of the estimators. Also, we demonstrated the proposed method using a real dataset.

引用

页码：651 / 682

页数：32

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