Competing Risks Quantile Regression at Work: In-depth Exploration of the Role of Public Child Support for the Duration of Maternity Leave

Stephan Dlugosz, Simon M. S. Lo, Ralf Wilke

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

168 Downloads (Pure)

Resumé

Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available.
OriginalsprogEngelsk
TidsskriftJournal of Applied Statistics
Vol/bind44
Udgave nummer1
Sider (fra-til)109-122
ISSN0266-4763
DOI
StatusUdgivet - 2017

Emneord

  • Dependent competing risks
  • Quantile regression
  • Quantile crossings

Citer dette

@article{b935d51c6fa04958913f8b14c7a11e89,
title = "Competing Risks Quantile Regression at Work: In-depth Exploration of the Role of Public Child Support for the Duration of Maternity Leave",
abstract = "Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available.",
keywords = "Dependent competing risks, Quantile regression, Quantile crossings, Dependent competing risks, Quantile regression, Quantile crossings",
author = "Stephan Dlugosz and Lo, {Simon M. S.} and Ralf Wilke",
year = "2017",
doi = "10.1080/02664763.2016.1164836",
language = "English",
volume = "44",
pages = "109--122",
journal = "Journal of Applied Statistics",
issn = "0266-4763",
publisher = "Routledge",
number = "1",

}

Competing Risks Quantile Regression at Work : In-depth Exploration of the Role of Public Child Support for the Duration of Maternity Leave. / Dlugosz, Stephan; Lo, Simon M. S. ; Wilke, Ralf.

I: Journal of Applied Statistics, Bind 44, Nr. 1, 2017, s. 109-122.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Competing Risks Quantile Regression at Work

T2 - In-depth Exploration of the Role of Public Child Support for the Duration of Maternity Leave

AU - Dlugosz, Stephan

AU - Lo, Simon M. S.

AU - Wilke, Ralf

PY - 2017

Y1 - 2017

N2 - Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available.

AB - Despite its emergence as a frequently used method for the empirical analysis of multivariate data, quantile regression is yet to become a mainstream tool for the analysis of duration data. We present a pioneering empirical study on the grounds of a competing risks quantile regression model. We use large-scale maternity duration data with multiple competing risks derived from German linked social security records to analyse how public policies are related to the length of economic inactivity of young mothers after giving birth. Our results show that the model delivers detailed insights into the distribution of transitions out of maternity leave. It is found that cumulative incidences implied by the quantile regression model differ from those implied by a proportional hazards model. To foster the use of the model, we make an R-package (cmprskQR) available.

KW - Dependent competing risks

KW - Quantile regression

KW - Quantile crossings

KW - Dependent competing risks

KW - Quantile regression

KW - Quantile crossings

U2 - 10.1080/02664763.2016.1164836

DO - 10.1080/02664763.2016.1164836

M3 - Journal article

VL - 44

SP - 109

EP - 122

JO - Journal of Applied Statistics

JF - Journal of Applied Statistics

SN - 0266-4763

IS - 1

ER -