Geometric Method of Determining Hazard for the Continuous Survival Function

A basic assumption in proportional intensity models is the proportionality, that each covariate has a multiplicative effect on the intensity. The proportionality assumption is a strong assumption which is not always necessarily reasonable and thus needs to be checked. The survival analysis often emp...

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Main Author: Bieszk-Stolorz Beata
Format: Article
Language:English
Published: Sciendo 2015-06-01
Series:Folia Oeconomica Stetinensia
Subjects:
Online Access:https://doi.org/10.1515/foli-2015-0031
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spelling doaj-23d9684902364455975d9222faa17bdc2021-09-05T20:45:01ZengSciendoFolia Oeconomica Stetinensia1898-01982015-06-01151223310.1515/foli-2015-0031foli-2015-0031Geometric Method of Determining Hazard for the Continuous Survival FunctionBieszk-Stolorz Beata0University of Szczecin Department of Econometrics and Statistics Faculty of Economics and Management Mickiewicza 64, 71-101 Szczecin, PolandA basic assumption in proportional intensity models is the proportionality, that each covariate has a multiplicative effect on the intensity. The proportionality assumption is a strong assumption which is not always necessarily reasonable and thus needs to be checked. The survival analysis often employs graphic methods to study hazard proportionality. In this paper a geometrical method for determining the value of the hazard function on the basis of the continuous survival function was proposed. This method can be used to compare the intensity of the event for objects belonging to two subgroups of the analysed population. If we have graphs of survival function, then an analysis of the tangents at a specific time and their roots enables us to find the intensity and to study the relationship between them for different subgroups. This method can also be useful when studying the proportionality of hazard. It is a condition for the use of the Cox proportional hazards model. The above method was used to evaluate the effect of unemployment benefit and gender on unemployment and on the intensity of finding a job.https://doi.org/10.1515/foli-2015-0031non-proportional hazardcontinuous survival functiongeometric methodunemployment
collection DOAJ
language English
format Article
sources DOAJ
author Bieszk-Stolorz Beata
spellingShingle Bieszk-Stolorz Beata
Geometric Method of Determining Hazard for the Continuous Survival Function
Folia Oeconomica Stetinensia
non-proportional hazard
continuous survival function
geometric method
unemployment
author_facet Bieszk-Stolorz Beata
author_sort Bieszk-Stolorz Beata
title Geometric Method of Determining Hazard for the Continuous Survival Function
title_short Geometric Method of Determining Hazard for the Continuous Survival Function
title_full Geometric Method of Determining Hazard for the Continuous Survival Function
title_fullStr Geometric Method of Determining Hazard for the Continuous Survival Function
title_full_unstemmed Geometric Method of Determining Hazard for the Continuous Survival Function
title_sort geometric method of determining hazard for the continuous survival function
publisher Sciendo
series Folia Oeconomica Stetinensia
issn 1898-0198
publishDate 2015-06-01
description A basic assumption in proportional intensity models is the proportionality, that each covariate has a multiplicative effect on the intensity. The proportionality assumption is a strong assumption which is not always necessarily reasonable and thus needs to be checked. The survival analysis often employs graphic methods to study hazard proportionality. In this paper a geometrical method for determining the value of the hazard function on the basis of the continuous survival function was proposed. This method can be used to compare the intensity of the event for objects belonging to two subgroups of the analysed population. If we have graphs of survival function, then an analysis of the tangents at a specific time and their roots enables us to find the intensity and to study the relationship between them for different subgroups. This method can also be useful when studying the proportionality of hazard. It is a condition for the use of the Cox proportional hazards model. The above method was used to evaluate the effect of unemployment benefit and gender on unemployment and on the intensity of finding a job.
topic non-proportional hazard
continuous survival function
geometric method
unemployment
url https://doi.org/10.1515/foli-2015-0031
work_keys_str_mv AT bieszkstolorzbeata geometricmethodofdetermininghazardforthecontinuoussurvivalfunction
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