IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v160y1997i3p491-505.html
   My bibliography  Save this article

Regression Modelling of Disease Risk in Relation to Point Sources

Author

Listed:
  • Peter Diggle
  • Sara Morris
  • Paul Elliott
  • Gavin Shaddick

Abstract

We describe a class of models for the investigation of possible raised risk of disease around putative sources of environmental pollution. An adaptation of the point process method suggested by Diggle and Rowlingson is presented, allowing the use of routinely available aggregated data and incorporating the more general distance–risk model suggested by Elliott and co‐workers. An application to data on cancers of the stomach around municipal solid waste incinerators is presented.

Suggested Citation

  • Peter Diggle & Sara Morris & Paul Elliott & Gavin Shaddick, 1997. "Regression Modelling of Disease Risk in Relation to Point Sources," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 491-505, September.
    • Handle: RePEc:bla:jorssa:v:160:y:1997:i:3:p:491-505
    DOI: 10.1111/j.1467-985X.1997.00076.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-985X.1997.00076.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-985X.1997.00076.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rachel C. Nethery & Yue Yang & Anna J. Brown & Francesca Dominici, 2020. "A causal inference framework for cancer cluster investigations using publicly available data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1253-1272, June.
    2. Alexandre Rodrigues & Peter Diggle & Renato Assuncao, 2010. "Semiparametric approach to point source modelling in epidemiology and criminology," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(3), pages 533-542, May.
    3. D. G. T. Denison & C. C. Holmes, 2001. "Bayesian Partitioning for Estimating Disease Risk," Biometrics, The International Biometric Society, vol. 57(1), pages 143-149, March.
    4. Hossain, Md. Monir & Lawson, Andrew B., 2009. "Approximate methods in Bayesian point process spatial models," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2831-2842, June.
    5. Álvaro Briz‐Redón & Jorge Mateu & Francisco Montes, 2022. "Identifying crime generators and spatially overlapping high‐risk areas through a nonlinear model: A comparison between three cities of the Valencian region (Spain)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(1), pages 97-120, February.
    6. Barry Trevelyan & Matthew Smallman‐Raynor & Andrew D. Cliff, 2005. "The spatial structure of epidemic emergence: geographical aspects of poliomyelitis in north‐eastern USA, July–October 1916," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(4), pages 701-722, November.
    7. Brian Conroy & Lance A. Waller & Ian D. Buller & Gregory M. Hacker & James R. Tucker & Mark G. Novak, 2023. "A Shared Latent Process Model to Correct for Preferential Sampling in Disease Surveillance Systems," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(3), pages 483-501, September.

    More about this item

    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:bla:jorssa:v:160:y:1997:i:3:p:491-505. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.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.