Study of Bootstrap Estimates in Cox Regression Model with Delayed Entry

Silvie Bělašková; Eva Fišerová; Sylvia Krupičková

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica (2013)

  • Volume: 52, Issue: 2, page 21-30
  • ISSN: 0231-9721

Abstract

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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.

How to cite

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Bělašková, Silvie, Fišerová, Eva, and Krupičková, Sylvia. "Study of Bootstrap Estimates in Cox Regression Model with Delayed Entry." Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica 52.2 (2013): 21-30. <http://eudml.org/doc/260825>.

@article{Bělašková2013,
abstract = {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.},
author = {Bělašková, Silvie, Fišerová, Eva, Krupičková, Sylvia},
journal = {Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica},
keywords = {Cox proportional regression model; Breslow method; delayed entry; observation study; mitral valve; Cox proportional regression model; Breslow method; delayed entry; observation study; mitral valve},
language = {eng},
number = {2},
pages = {21-30},
publisher = {Palacký University Olomouc},
title = {Study of Bootstrap Estimates in Cox Regression Model with Delayed Entry},
url = {http://eudml.org/doc/260825},
volume = {52},
year = {2013},
}

TY - JOUR
AU - Bělašková, Silvie
AU - Fišerová, Eva
AU - Krupičková, Sylvia
TI - Study of Bootstrap Estimates in Cox Regression Model with Delayed Entry
JO - Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
PY - 2013
PB - Palacký University Olomouc
VL - 52
IS - 2
SP - 21
EP - 30
AB - 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.
LA - eng
KW - Cox proportional regression model; Breslow method; delayed entry; observation study; mitral valve; Cox proportional regression model; Breslow method; delayed entry; observation study; mitral valve
UR - http://eudml.org/doc/260825
ER -

References

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