Survival Modelling of Repeated Events Using the Example of Changes in the Place of Employment
DOI:
https://doi.org/10.18778/0208-6018.342.10Keywords:
employment, repeated events, exponential model, Weibull model, models with random effectsAbstract
This paper concerns the issue of survival modelling in the case of repeated events. In the modelling of this type of events, attention should be paid to the existence of dependence among the analysed durations, as well as the occurrence of unobserved heterogeneity. One of the ways to include these aspects in the analysis is to use models with random effects. The primary objective of this paper is to present the application of such models to analyse changes in the place of employment. The duration of individual periods of employment for the surveyed employees was modelled. The approach used made it possible to identify factors influencing decisions on job changes, but also to assess the risk of occurrence of events such as termination of employment, and to examine the impact of unobserved heterogeneity on the results of the estimations.
Downloads
References
Allison P. D. (2010), Survival Analysis Using SAS: A Practical Guide, Second Edition, SAS Institute Inc., Cary.
Google Scholar
Balbo N., Billari F. C., Mills M. (2013), Fertility in Advanced Societies: A Review of Research, “European Journal of Population”, vol. 29, pp. 1–38.
Google Scholar
Bieszk‑Stolorz B. (2018), Analysis of the duration in unemployment with use of the regression models for the recurrent events, “Research Papers Of Wrocław University Of Economics”, vol. 507, pp. 21–29.
Google Scholar
Cox D. R., Oakes D. (1984), Analysis of Survival Data, Chapman and Hall, London.
Google Scholar
CSO (2016), Monitoring rynku pracy. Kwartalna informacja o rynku pracy, Warszawa.
Google Scholar
Fan J., Li R. (2002), Variable selection for Cox’s proportional hazards model and frailty model, “Annals of Statistics”, vol. 30, pp. 74–99.
Google Scholar
Generations and Gender Programme, http://www.ggp‑i.org/ [accessed: 10.12.2018].
Google Scholar
Giannelli G. C., Jaenichen U., Rothe T. (2016), The evolution of job stability and wages after the implementation of the Hartz reforms, “Journal for Labour Market Research”, vol. 49, no. 3, pp. 269–294.
Google Scholar
Grzenda W. (2017), Modelling the duration of the first job using Bayesian accelerated failure time models, “Acta Universitatis Lodziensis. Folia Oeconomica”, vol. 4, no. 330, pp. 19–38.
Google Scholar
Gutierrez R. G. (2002), Parametric frailty and shared frailty survival models, “Stata Journal”, vol. 2, no. 1, pp. 22–44.
Google Scholar
Hougaard P. (1991), Modelling heterogeneity in survival data, “Journal of Applied Probability”, vol. 28, no. 3, pp. 695–701.
Google Scholar
Hougaard P. (1995), Frailty models for survival data, “Lifetime Data Analysis”, vol. 1, no. 3, pp. 255–273.
Google Scholar
Kleinbaum D. G., Klein M. (2006), Survival Analysis: A Self‑Learning Text, Springer Science & Business Media, New York.
Google Scholar
Kotowska I. E., Sztanderska U., Wóycicka I. (eds.) (2007), Aktywność zawodowa i edukacyjna a obowiązki rodzinne w Polsce w świetle badań empirycznych, Wydawnictwo Naukowe Scholar, Warszawa.
Google Scholar
Landmesser J. (2013), Wykorzystanie metod analizy czasu trwania do badania aktywności ekonomicznej ludności w Polsce, Wydawnictwo SGGW, Warszawa.
Google Scholar
Miller Jr R. G. (2011), Survival analysis, vol. 66, John Wiley & Sons, Hoboken.
Google Scholar
Morris C., Christiansen C. (1995), Fitting Weibull duration models with random effects, “Lifetime Data Analysis”, vol. 1, no. 4, pp. 347–359.
Google Scholar
Sochacka K. (2012), Skuteczne rozwiązanie stosunku pracy z pracownikiem, C. H. Beck, Warszawa.
Google Scholar
Sztanderska U. (2005), Aktywność zawodowa kobiet w Polsce. Jakie szanse? Jakie rezultaty?, [in:] I. Wóycicka (ed.), Szanse na wzrost dzietności – jaka polityka rodzinna?, Polskie Forum Strategii Lizbońskiej, Niebieskie Księgi, Gdańsk.
Google Scholar
Tanova C., Holtom B. C. (2008), Using job embeddedness factors to explain voluntary turnover in four European countries, “The International Journal of Human Resource Management”, vol. 19, no. 9, pp. 1553–1568.
Google Scholar
Wienke A. (2011), Frailty Models in Survival Analysis, CRC Press, Boca Raton.
Google Scholar
Willekens F. (1999), The Life course: Models and analysis, [in:] L. Van Wissen, P. Dykstra (eds.), Population Issues: An Interdisciplinary Approach, Kluwer/Plenum Publisher, New York.
Google Scholar