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Unshared and Shared Frailty Models

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  • Nihal Ata Tutkun
  • Diren Yeğen

Abstract

The Cox regression model which is commonly used in survival analysis is established under the proportional hazards assumption. However cases in which the data shows heterogeneity come across in studies. In this case, heterogeneity should be explained in order to make the interpretations more effective which were obtained depending on the model. Frailty models are one of the survival analysis methods which were developed for explaining heterogeneity. In this study, frailty models are examined theoretically and were applied to the lung cancer data. The unshared frailty model has been used to explain the difference between general risk and momentary risk of individuals in the data set. As for comparing the momentary risk between individuals with various levels of explanatory variables with other individuals, shared frailty models have been used.

Suggested Citation

  • Nihal Ata Tutkun & Diren Yeğen, 2016. "Unshared and Shared Frailty Models," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 4(1), pages 45-56, June.
    • Handle: RePEc:anm:alpnmr:v:4:y:2016:i:1:p:45-56
    DOI: http://dx.doi.org/10.17093/aj.2016.4.1.5000163276
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    References listed on IDEAS

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    1. Kheiri, Soleiman & Kimber, Alan & Reza Meshkani, Mohammad, 2007. "Bayesian analysis of an inverse Gaussian correlated frailty model," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5317-5326, July.
    2. Roberto G. Gutierrez, 2002. "Parametric frailty and shared frailty survival models," Stata Journal, StataCorp LP, vol. 2(1), pages 22-44, February.
    3. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
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    More about this item

    Keywords

    Cox Regression; Frailty Models; Nonproportional Hazards; Parametric Regression Models; Survival Analysis;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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