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A stochastic frontier approach to survival analysis

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  • K. Suresh Chandra
  • G. Gopal
  • M. Ramadurai

Abstract

In spite of the best set of covariates and statistical tools for the survival analysis, there are instances when experts do not rule out the existence of many non-observable factors that could influence the survival probability of an individual. The fact that every human body, sick or otherwise, strives to maximize time to death, renders the stochastic frontier analysis (vide 2) as a meaningful tool to measure the unobservable individual-specific deficiency factor that accounts for the difference between the optimal and observed survival times. In this paper, given the survival data, an attempt is made to measure the deficiency factor for each individual in the data on adopting the stochastic frontier analysis. Such an attempt to quantify the effect of these unobservable factors can provide ample scope for further research in bio-medical studies. The utility of these estimates in the survival analysis is also highlighted using a real-life data.

Suggested Citation

  • K. Suresh Chandra & G. Gopal & M. Ramadurai, 2013. "A stochastic frontier approach to survival analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(6), pages 1362-1371, June.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:6:p:1362-1371
    DOI: 10.1080/02664763.2013.785498
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    References listed on IDEAS

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    1. Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633, January.
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    Cited by:

    1. Nikolskiy, Ilya & Furmanov, Kirill, 2023. "Assessing the accuracy of efficiency rankings obtained from a stochastic frontier model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 71, pages 128-142.

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