IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this article

How to study cognitive decision algorithms: The case of the priority heuristic

Listed author(s):
  • Klaus Fiedler
Registered author(s):

    Although the priority heuristic (PH) is conceived as a cognitive-process model, some of its critical process assumptions remain to be tested. The PH makes very strong ordinal and quantitative assumptions about the strictly sequential, non-compensatory use of three cues in choices between lotteries: (1) the difference between worst outcomes, (2) the difference in worst-case probabilities, and (3) the best outcome that can be obtained. These aspects were manipulated orthogonally in the present experiment. No support was found for the PH. Although the main effect of the primary worst-outcome manipulation was significant, it came along with other effects that the PH excludes. A strong effect of the secondary manipulation of worst-outcome probabilities was not confined to small differences in worst-outcomes; it was actually stronger for large worst-outcome differences. Overall winning probabilities that the PH ignores exerted a systematic influence. The overall rate of choices correctly predicted by the PH was close to chance, although high inter-judge agreement reflected systematic responding. These findings raise fundamental questions about the theoretical status of heuristics as fixed modules.

    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: no

    File URL:
    Download Restriction: no

    Article provided by Society for Judgment and Decision Making in its journal Judgment and Decision Making.

    Volume (Year): 5 (2010)
    Issue (Month): 1 (February)
    Pages: 21-32

    in new window

    Handle: RePEc:jdm:journl:v:5:y:2010:i:1:p:21-32
    Contact details of provider:

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    in new window

    1. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Rosenthal,Robert, 2009. "Judgment Studies," Cambridge Books, Cambridge University Press, number 9780521101479, March.
    Full references (including those not matched with items on IDEAS)

    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:jdm:journl:v:5:y:2010:i:1:p:21-32. 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: (Jonathan Baron)

    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.