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Survival with Random Effect

Author

Listed:
  • Jonas Šiaulys

    (Institute of Mathematics, Vilnius University, Naugarduko 24, LT-032225 Vilnius, Lithuania
    These authors contributed equally to this work.)

  • Rokas Puišys

    (Institute of Mathematics, Vilnius University, Naugarduko 24, LT-032225 Vilnius, Lithuania
    These authors contributed equally to this work.)

Abstract

The article focuses on mortality models with a random effect applied in order to evaluate human mortality more precisely. Such models are called frailty or Cox models. The main assertion of the paper shows that each positive random effect transforms the initial hazard rate (or density function) to a new absolutely continuous survival function. In particular, well-known Weibull and Gompertz hazard rates and corresponding survival functions are analyzed with different random effects. These specific models are presented with detailed calculations of hazard rates and corresponding survival functions. Six specific models with a random effect are applied to the same data set. The results indicate that the accuracy of the model depends on the data under consideration.

Suggested Citation

  • Jonas Šiaulys & Rokas Puišys, 2022. "Survival with Random Effect," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:7:p:1097-:d:782000
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    References listed on IDEAS

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