Poisson excess relative risk modelsnew implementations and software

  1. Manuel Higueras 1
  2. Adam Howes 2
  1. 1 Departamento de Matem ́ aticas y Computación, Universidad de La Rioja
  2. 2 Basque Center for Applied Mathematics
    info

    Basque Center for Applied Mathematics

    Bilbao, España

    ROR 03b21sh32

Revista:
Sort: Statistics and Operations Research Transactions

ISSN: 1696-2281

Any de publicació: 2018

Volum: 42

Número: 2

Pàgines: 237-252

Tipus: Article

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DOI: 10.2436/20.8080.02.76 WoS: WOS:000454146400006 DIALNET GOOGLE SCHOLAR lock_openAccés obert editor

Altres publicacions en: Sort: Statistics and Operations Research Transactions

Objectius de Desenvolupament Sostenible

Resum

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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Informació de finançament

This research was supported by the Basque Government through the BERC 360 2014-2017 and the Spanish Ministry of Economy and Competitiveness MINECO and FEDER: BCAM Severo Ochoa excellence accreditation SEV-2013-0323 and MINECO Challenges MTM2017-82379-R.

Finançadors

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