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Application of the Cox proportional hazards model and competing risks models to critical illness insurance data

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F21%3A39917550" target="_blank" >RIV/00216275:25410/21:39917550 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://onlinelibrary.wiley.com/doi/10.1002/sam.11532" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/sam.11532</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/sam.11532" target="_blank" >10.1002/sam.11532</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Application of the Cox proportional hazards model and competing risks models to critical illness insurance data

  • Popis výsledku v původním jazyce

    A commercial insurance company in the Czech Republic provided data on critical illness insurance. The survival analysis was used to study the influence of the gender of an insured person, the age at which the person entered into an insurance contract, and the region where the insured person lived on the occurrence of an insured event. The main goal of the research was to investigate whether the influence of explanatory variables is estimated differently when two different approaches of analysis are used. The two approaches used were (1) the Cox proportional hazard model that does not assign a specific cause, such as a certain diagnosis, to a critical illness insured event and (2) the competing risks models. Regression models related to these approaches were estimated by R software. The results, which are discussed and compared in the paper, show that insurance companies might benefit from offering policies that consider specific diagnoses as the cause of insured events. They also show that in addition to age, the gender of the client plays a key role in the occurrence of such insured events.

  • Název v anglickém jazyce

    Application of the Cox proportional hazards model and competing risks models to critical illness insurance data

  • Popis výsledku anglicky

    A commercial insurance company in the Czech Republic provided data on critical illness insurance. The survival analysis was used to study the influence of the gender of an insured person, the age at which the person entered into an insurance contract, and the region where the insured person lived on the occurrence of an insured event. The main goal of the research was to investigate whether the influence of explanatory variables is estimated differently when two different approaches of analysis are used. The two approaches used were (1) the Cox proportional hazard model that does not assign a specific cause, such as a certain diagnosis, to a critical illness insured event and (2) the competing risks models. Regression models related to these approaches were estimated by R software. The results, which are discussed and compared in the paper, show that insurance companies might benefit from offering policies that consider specific diagnoses as the cause of insured events. They also show that in addition to age, the gender of the client plays a key role in the occurrence of such insured events.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10103 - Statistics and probability

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2021

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Statistical Analysis and Data Mining

  • ISSN

    1932-1864

  • e-ISSN

  • Svazek periodika

    14

  • Číslo periodika v rámci svazku

    4

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    10

  • Strana od-do

    342-351

  • Kód UT WoS článku

    000659464700001

  • EID výsledku v databázi Scopus

    2-s2.0-85107411235