Survival with Random Effect

Jonas Šiaulys and Rokas Puišys
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Jonas Šiaulys: Institute of Mathematics, Vilnius University, Naugarduko 24, LT-032225 Vilnius, Lithuania
Rokas Puišys: Institute of Mathematics, Vilnius University, Naugarduko 24, LT-032225 Vilnius, Lithuania

Mathematics, 2022, vol. 10, issue 7, 1-17

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.

Keywords: mortality; survival model; survival function; random effect; force of mortality (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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