IDEAS home Printed from
MyIDEAS: Login to save this article or follow this journal

Malformed frogs: Bayesian and random-effect model analyses

  • Jon E. Anderson
  • David M. Hoppe
Registered author(s):

    Historical data (1958–1963) on frog malformations in Minnesota, USA, are compared to malformation data collected from 1996 to 1999, at many of the same collection sites, to investigate malformation risk changes between the study periods. We initially consider Mantel-Haenszel and simple logistic regression analyses. Potential variation in risk across data collection sites lead to random-effect logistic regression and hierarchical Bayesian models. We find clear evidence of increased malformation risk in the 1990s data collection period. The random-effect logistic regression and Bayesian logistic regression analyses produce similar point estimates of relative risk, and uncertainty, but Bayesian models allow analysts to view the impact of additional information on the inferences. Bayesian analyses programs in WinBUGS and SAS are provided.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Inderscience Enterprises Ltd in its journal Int. J. of Data Analysis Techniques and Strategies.

    Volume (Year): 2 (2010)
    Issue (Month): 2 ()
    Pages: 103-121

    in new window

    Handle: RePEc:ids:injdan:v:2:y:2010:i:2:p:103-121
    Contact details of provider: Web page:

    No references listed on IDEAS
    You can help add them by filling out this form.

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:ids:injdan:v:2:y:2010:i:2:p:103-121. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Graham Langley)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.