Literature DB >> 19933879

The competing risks illness-death model under cross-sectional sampling.

Micha Mandel1.   

Abstract

The competing risks illness-death model describes the dynamics of healthy subjects who may move to an "illness" state before entering into one of several competing terminal states. A motivating example concerns patients in a hospital who may acquire infections during their stay, where the competing terminal states are discharged alive and death in the hospital. We consider a cross-sectional sampling of independent competing risks illness-death processes in which data are subject to length bias and censoring and develop estimators for functionals of the underlying distribution such as the joint probability of the terminal state and illness (infection) and cumulative incidence functions. We apply the methodology to infection data obtained in a cross-sectional study of patients hospitalized in intensive care units.

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Year:  2009        PMID: 19933879     DOI: 10.1093/biostatistics/kxp048

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  5 in total

1.  Nonparametric estimation in the illness-death model using prevalent data.

Authors:  Bella Vakulenko-Lagun; Micha Mandel; Yair Goldberg
Journal:  Lifetime Data Anal       Date:  2016-06-28       Impact factor: 1.588

2.  Semiparametric modeling of grouped current duration data with preferential reporting.

Authors:  Alexander C McLain; Rajeshwari Sundaram; Marie Thoma; Germaine M Buck Louis
Journal:  Stat Med       Date:  2014-05-27       Impact factor: 2.373

3.  Bayesian gamma frailty models for survival data with semi-competing risks and treatment switching.

Authors:  Yuanye Zhang; Ming-Hui Chen; Joseph G Ibrahim; Donglin Zeng; Qingxia Chen; Zhiying Pan; Xiaodong Xue
Journal:  Lifetime Data Anal       Date:  2013-03-30       Impact factor: 1.588

4.  Inverse Probability Weighting Enhances Absolute Risk Estimation in Three Common Study Designs of Nosocomial Infections.

Authors:  Maja von Cube; Derek Hazard; James Balmford; Paulina Staus; Sam Doerken; Ksenia Ershova; Martin Wolkewitz
Journal:  Clin Epidemiol       Date:  2022-09-14       Impact factor: 5.814

5.  Length-biased semi-competing risks models for cross-sectional data: an application to current duration of pregnancy attempt data.

Authors:  Alexander C McLain; Siyuan Guo; Jiajia Zhang; Thoma Marie
Journal:  Ann Appl Stat       Date:  2021-07-12       Impact factor: 1.959

  5 in total

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