The Cox Proportional Hazard Model for Different Methods of Encryption of Variables

Iwona Markowicz; Beata Stolorz

doi:https://doi.org/10.59139/ps.2009.02.7

Iwona Markowicz Uniwersytet Szczeciński , Beata Stolorz Uniwersytet Szczeciński Przegląd Statystyczny. Statistical Review, vol. 56, 2009, 2, pages: 106-115 Published online: 30 June 2009 DOI https://doi.org/10.59139/ps.2009.02.7

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ARTICLE

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ABSTRACT

Methods of survival analysis are more and more often used in analysis of social and economic occurrences. Due to lack of distributional information regarding the random variable, much attention is put on non-parametric or semi-parametric models. They are more and more commonly used for analysis of occurrences different than life expectancy. The condition of use of models of survival analysis is appropriate database that makes possible estimation of duration time of defined state for particular elements of analysed population. They are usually retrospective analyses with use of records. The example of such database is unemployment records. The article presents results of analysis of influence of encryption of variables on estimation of parameters of the Cox proportional hazard model and their interpretation. The authors also presented correlation between parameters of the model estimated for the data encrypted in two ways. The cohort consisted of the unemployed persons unregistered in specific period. Sub-clusters were allocated with respect to age that is a determinant of period of waiting for a job.

KEYWORDS

survival analysis, semi-parametric models, Cox regression model, encryption

REFERENCES

[1] Bednarski T., [2005], Ocena przydatności danych Bael dla charakterystyki rozkładu czasu poszukiwania pracy na przykładzie danych z lat 2001-2002, Studia Ekonomiczne, nr 4, Instytut Nauk Ekonomicznych PAN, Warszawa.

[2] Colett D., [2003], Modelling Survival Data in Medical Research, Chapman & Hall/CRC, Boca Raton, Floryda.

[3] Cox D.R., Oakes D., [1984], Analysis of Survival Data, Chapman and Hall, London.

[4] Frątczak E., Gach-Ciepiela U., Babiker H., [2005], Analiza historii zdarzeń. Elementy teorii, wybrane przykłady zastosowań, SGH, Warszawa.

[5] Hosmer D.W., Lemeshow S., [1999], Applied Survival Analysis. Regression Modeling of Time to Event Data, John Wiley & Sons, INC, New York.

[6] Hozer J. (red.), [2002], Badania statystyczne w ubezpieczeniach, Wydawnictwo Naukowe Uniwersytetu Szczecińskiego, Szczecin.

[7] Markowicz I., Stolorz B., [2007], Determinants of Labour Seeking Time Resulting From Labour Demand on Szczecin Labour Market, The labour demand in the modern economy, Economics & Competition Policy, No. 10, Katedra Mikroekonomii Uniwersytetu Szczecińskiego, Szczecin.

[8] Rossa A., [2005], Metody estymacji rozkładu czasu trwania zjawisk dla danych cenzurowanych oraz ich zastosowania, Wydawnictwo Uniwersytetu Łódzkiego, Łódź.