IDEAS home Printed from https://ideas.repec.org/p/ude/wpaper/0426.html

From smoking scenarios to lung cancer mortality: sequential bayesian APC projections

Author

Listed:
  • Manuel Flores

Abstract

This working paper develops a sequential Bayesian age–period–cohort (APC) framework for projecting cancer mortality under alternative smoking scenarios using aggregate population data. The framework estimates smoking-prevalence surfaces, reconstructs cohort smoking states, maps effective exposure into incidence through external relative risks and risk-reversion schedules, and translates projected incidence into mortality using post-diagnosis mortality schedules. Simulation results evaluate recovery of known scenario effects, and the empirical illustration uses lung-cancer data from Uruguay with an extension to nine smoking-related cancer sites.

Suggested Citation

  • Manuel Flores, "undated". "From smoking scenarios to lung cancer mortality: sequential bayesian APC projections," Documentos de Trabajo (working papers) 0426, Department of Economics - dECON.
    • Handle: RePEc:ude:wpaper:0426
    as

    Download full text from publisher

    File URL: https://hdl.handle.net/20.500.12008/56099
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ude:wpaper:0426. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Andrea Doneschi or the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/derauuy.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.