Poisson excess relative risk models: new implementations and software

• Manuel Higueras ^[1] ; Adam Howes ^[2]
  1. [1] Universidad de La Rioja

     Universidad de La Rioja

     Logroño, España

     
  2. [2] Basque Center for Applied Mathematics

     Basque Center for Applied Mathematics

     Bilbao, España

     
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 42, Nº. 2, 2018, págs. 237-252
• Idioma: inglés
• DOI: 10.2436/20.8080.02.76
• Enlaces
  • Texto completo (pdf)
• Resumen

  • Two new implementations for fitting Poisson excess relative risk methods are proposed for as- sumed simple models. This allows for estimation of the excess relative risk associated with a unique exposure, where the background risk is modelled by a unique categorical variable, for example gender or attained age levels. Additionally, it is shown how to fit general Poisson linear relative risk models in R. Both simple methods and the R fitting are illustrated in three examples.

    The first two examples are from the radiation epidemiology literature. Data in the third example are randomly generated with the purpose of sharing it jointly with the R scripts.

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