IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v91y2004i1p15-25.html
   My bibliography  Save this article

Equivalence of prospective and retrospective models in the Bayesian analysis of case-control studies

Author

Listed:
  • Shaun R. Seaman

Abstract

The natural likelihood to use for a case-control study is a 'retrospective' likelihood, i.e. a likelihood based on the probability of exposure given disease status. Prentice & Pyke (1979) showed that, when a logistic regression form is assumed for the probability of disease given exposure, the maximum likelihood estimators and asymptotic covariance matrix of the log odds ratios obtained from the retrospective likelihood are the same as those obtained from the 'prospective' likelihood, i.e. that based on probability of disease given exposure. We prove a similar result for the posterior distribution of the log odds ratios in a Bayesian analysis. This means that the Bayesian analysis of case-control studies may be done using a relatively simple model, the logistic regression model, which treats data as though generated prospectively and which does not involve nuisance parameters for the exposure distribution. Copyright Biometrika Trust 2004, Oxford University Press.

Suggested Citation

  • Shaun R. Seaman, 2004. "Equivalence of prospective and retrospective models in the Bayesian analysis of case-control studies," Biometrika, Biometrika Trust, vol. 91(1), pages 15-25, March.
    • Handle: RePEc:oup:biomet:v:91:y:2004:i:1:p:15-25
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Shi Li & Bhramar Mukherjee & Stuart Batterman & Malay Ghosh, 2013. "Bayesian Analysis of Time-Series Data under Case-Crossover Designs: Posterior Equivalence and Inference," Biometrics, The International Biometric Society, vol. 69(4), pages 925-936, December.
    2. Mukherjee, Bhramar & Liu, Ivy, 2009. "A note on bias due to fitting prospective multivariate generalized linear models to categorical outcomes ignoring retrospective sampling schemes," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 459-472, March.
    3. Dhiman Bhadra & Michael J. Daniels & Sungduk Kim & Malay Ghosh & Bhramar Mukherjee, 2012. "A Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case–Control Studies," Biometrics, The International Biometric Society, vol. 68(2), pages 361-370, June.

    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:oup:biomet:v:91:y:2004:i:1:p:15-25. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/biomet .

    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.