Revistes Publicacions URV: SORT - Statistics and Operations Research Transactions> 2018

Poisson excess relative risk models: new implementations and software

  • Identification data

    Identifier: RP:3073
    Handle: http://hdl.handle.net/20.500.11797/RP3073
  • Authors:

    Howes, Adam
    Higueras, Manuel
  • Others:

    URV's Author/s: Howes, Adam Higueras, Manuel
    Keywords: Radiation epidemiology, Poisson non-linear regression, improper priors, R programming
    Abstract: Two new implementations for fitting Poisson excess relative risk methods are proposed for assumed 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.
    Journal publication year: 2018
    Publication Type: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article
  • Keywords:

    Radiation epidemiology, Poisson non-linear regression, improper priors, R programming
  • Documents:

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