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On estimation of linear transformation models with nested case–control sampling

Nested case–control (NCC) sampling is widely used in large epidemiological cohort studies for its cost effectiveness, but its data analysis primarily relies on the Cox proportional hazards model. In this paper, we consider a family of linear transformation models for analyzing NCC data and propose a... Full description

Journal Title: Lifetime Data Analysis 2012, Vol.18(1), pp.80-93
Main Author: Lu, Wenbin
Other Authors: Liu, Mengling
Format: Electronic Article Electronic Article
Language: English
Subjects:
Quelle: Springer Science & Business Media B.V.
ID: ISSN: 1380-7870 ; E-ISSN: 1572-9249 ; DOI: 10.1007/s10985-011-9203-3
Link: http://dx.doi.org/10.1007/s10985-011-9203-3
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recordid: springer_jour10.1007/s10985-011-9203-3
title: On estimation of linear transformation models with nested case–control sampling
format: Article
creator:
  • Lu, Wenbin
  • Liu, Mengling
subjects:
  • Linear transformation models
  • Nested case–control sampling
  • Weighted estimating equation
ispartof: Lifetime Data Analysis, 2012, Vol.18(1), pp.80-93
description: Nested case–control (NCC) sampling is widely used in large epidemiological cohort studies for its cost effectiveness, but its data analysis primarily relies on the Cox proportional hazards model. In this paper, we consider a family of linear transformation models for analyzing NCC data and propose an inverse selection probability weighted estimating equation method for inference. Consistency and asymptotic normality of our estimators for regression coefficients are established. We show that the asymptotic variance has a closed analytic form and can be easily estimated. Numerical studies are conducted to support the theory and an application to the Wilms’ Tumor Study is also given to illustrate the methodology.
language: eng
source: Springer Science & Business Media B.V.
identifier: ISSN: 1380-7870 ; E-ISSN: 1572-9249 ; DOI: 10.1007/s10985-011-9203-3
fulltext: fulltext
issn:
  • 1572-9249
  • 15729249
  • 1380-7870
  • 13807870
url: Link


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subjectLinear transformation models ; Nested case–control sampling ; Weighted estimating equation
descriptionNested case–control (NCC) sampling is widely used in large epidemiological cohort studies for its cost effectiveness, but its data analysis primarily relies on the Cox proportional hazards model. In this paper, we consider a family of linear transformation models for analyzing NCC data and propose an inverse selection probability weighted estimating equation method for inference. Consistency and asymptotic normality of our estimators for regression coefficients are established. We show that the asymptotic variance has a closed analytic form and can be easily estimated. Numerical studies are conducted to support the theory and an application to the Wilms’ Tumor Study is also given to illustrate the methodology.
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abstractNested case–control (NCC) sampling is widely used in large epidemiological cohort studies for its cost effectiveness, but its data analysis primarily relies on the Cox proportional hazards model. In this paper, we consider a family of linear transformation models for analyzing NCC data and propose an inverse selection probability weighted estimating equation method for inference. Consistency and asymptotic normality of our estimators for regression coefficients are established. We show that the asymptotic variance has a closed analytic form and can be easily estimated. Numerical studies are conducted to support the theory and an application to the Wilms’ Tumor Study is also given to illustrate the methodology.
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