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Title: Study of Bootstrap Estimates in Cox Regression Model with Delayed Entry (English)
Author: Bělašková, Silvie
Author: Fišerová, Eva
Author: Krupičková, Sylvia
Language: English
Journal: Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
ISSN: 0231-9721
Volume: 52
Issue: 2
Year: 2013
Pages: 21-30
Summary lang: English
Category: math
Summary: In most clinical studies, patients are observed for extended time periods to evaluate influences in treatment such as drug treatment, approaches to surgery, etc. The primary event in these studies is death, relapse, adverse drug reaction, or development of a new disease. The follow-up time may range from few weeks to many years. Although these studies are long term, the number of observed events is small. Longitudinal studies have increased the importance of statistical methods for time-to event data that can incorporate time-dependent covariates. The Cox proportional regression model is a widely used method. It is a statistical technique for exploring the relationship between the survival of a patient and several explanatory variables. We apply Cox regression models when right censoring and delayed entry survival data are considered. Su and Wang (2012) stated that delayed entry produced biased sample. In the paper we present how re-sampling together with effect of delayed entry affect estimated parameters. The possibilities as well as limitations of this approach are demonstrated through the retrospective study of mitral valve replacement in children under 18 years. (English)
Keyword: Cox proportional regression model
Keyword: Breslow method
Keyword: delayed entry
Keyword: observation study
Keyword: mitral valve
MSC: 62G09
MSC: 62N01
MSC: 62N02
MSC: 62P10
idZBL: Zbl 06296011
idMR: MR3202376
Date available: 2013-12-18T15:19:59Z
Last updated: 2014-07-30
Stable URL:
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