IDEAS home Printed from https://ideas.repec.org/a/eee/intell/v84y2021ics0160289620300945.html
   My bibliography  Save this article

Further evidence that the worst performance rule is a special case of the correlation of sorted scores rule

Author

Listed:
  • Sorjonen, Kimmo
  • Madison, Guy
  • Hemmingsson, Tomas
  • Melin, Bo
  • Ullén, Fredrik

Abstract

According to the worst performance rule (WPR), the correlations between intelligence and sorted performances, for example on reaction time tasks, should strengthen from the best to the worst performance. A commonly proposed explanation for the WPR is that poor performances reflect lapses of attention that are particularly strongly related to intelligence. The correlation of sorted scores rule (CSSR), on the other hand, claims that the WPR arises due to certain statistical properties of the data. Specifically, the magnitude of intelligence-performance correlations will change with the rank order of the test when intelligence is correlated with the within-individual standard deviation (WISD) of the tests. If the latter correlation is negative, a WPR is seen, i.e. intelligence-performance correlations will be lower for tests with higher rank order. If the intelligence-WISD correlation were positive, however, intelligence-performance correlations would instead increase with test rank order. In the present study, through strategic slicing of two samples (N = 1485, and N = 43,987, respectively), we created subsamples with a large range of intelligence-WISD correlations. In accordance with the CSSR, but not the WPR, the association between intelligence-performance correlations and test rank order was found to reflect the intelligence-WISD correlation of the subsample. This supports that the WPR might be a special case of the more general CSSR and that the WPR is crucially dependent on intelligence-WISD correlations. The findings also indicate that the predictions made by the CSSR generalize to other predictors besides intelligence and to other outcomes besides reaction time.

Suggested Citation

  • Sorjonen, Kimmo & Madison, Guy & Hemmingsson, Tomas & Melin, Bo & Ullén, Fredrik, 2021. "Further evidence that the worst performance rule is a special case of the correlation of sorted scores rule," Intelligence, Elsevier, vol. 84(C).
  • Handle: RePEc:eee:intell:v:84:y:2021:i:c:s0160289620300945
    DOI: 10.1016/j.intell.2020.101516
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160289620300945
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.intell.2020.101516?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sorjonen, Kimmo & Madison, Guy & Melin, Bo & Ullén, Fredrik, 2020. "The Correlation of Sorted Scores Rule," Intelligence, Elsevier, vol. 80(C).
    2. Brown, William W & Reynolds, Morgan O, 1975. "A Model of IQ, Occupaton, and Earnings," American Economic Review, American Economic Association, vol. 65(5), pages 1002-1007, December.
    3. Wallert, John & Ekman, Urban & Westman, Eric & Madison, Guy, 2017. "The worst performance rule with elderly in abnormal cognitive decline," Intelligence, Elsevier, vol. 64(C), pages 9-17.
    4. Schubert, Anna-Lena, 2019. "A meta-analysis of the worst performance rule," Intelligence, Elsevier, vol. 73(C), pages 88-100.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sorjonen, Kimmo & Madison, Guy & Melin, Bo & Ullén, Fredrik, 2020. "The Correlation of Sorted Scores Rule," Intelligence, Elsevier, vol. 80(C).
    2. Ociepka, Michał & Kałamała, Patrycja & Chuderski, Adam, 2022. "High individual alpha frequency brains run fast, but it does not make them smart," Intelligence, Elsevier, vol. 92(C).
    3. Schubert, Anna-Lena, 2019. "A meta-analysis of the worst performance rule," Intelligence, Elsevier, vol. 73(C), pages 88-100.
    4. Hilger, Kirsten & Spinath, Frank M. & Troche, Stefan & Schubert, Anna-Lena, 2022. "The biological basis of intelligence: Benchmark findings," Intelligence, Elsevier, vol. 93(C).
    5. Frischkorn, Gidon T. & Wilhelm, Oliver & Oberauer, Klaus, 2022. "Process-oriented intelligence research: A review from the cognitive perspective," Intelligence, Elsevier, vol. 94(C).

    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:eee:intell:v:84:y:2021:i:c:s0160289620300945. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc 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 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    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.