IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v46y2017i14p6774-6781.html
   My bibliography  Save this article

Relative effect sizes for measures of risk

Author

Listed:
  • Jake Olivier
  • Warren L. May
  • Melanie L. Bell

Abstract

Effect sizes are an important component of experimental design, data analysis, and interpretation of statistical results. In some situations, an effect size of clinical or practical importance may be unknown to the researcher. In other situations, the researcher may be interested in comparing observed effect sizes to known standards to quantify clinical importance. In these cases, the notion of relative effect sizes (small, medium, large) can be useful as benchmarks. Although there is generally an extensive literature on relative effect sizes for continuous data, little of this research has focused on relative effect sizes for measures of risk that are common in epidemiological or biomedical studies. The aim of this paper, therefore, is to extend existing relative effect sizes to the relative risk, odds ratio, hazard ratio, rate ratio, and Mantel–Haenszel odds ratio for related samples. In most scenarios with equal group allocation, effect sizes of 1.22, 1.86, and 3.00 can be taken as small, medium, and large, respectively. The odds ratio for a non rare event is a notable exception and modified relative effect sizes are 1.32, 2.38, and 4.70 in that situation.

Suggested Citation

  • Jake Olivier & Warren L. May & Melanie L. Bell, 2017. "Relative effect sizes for measures of risk," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(14), pages 6774-6781, July.
  • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:14:p:6774-6781
    DOI: 10.1080/03610926.2015.1134575
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2015.1134575
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03610926.2015.1134575?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.

    Citations

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


    Cited by:

    1. repec:spo:wpmain:info:hdl:2441/2prlafc9459u7oc5p9pdolft63 is not listed on IDEAS
    2. repec:hal:spmain:info:hdl:2441/2prlafc9459u7oc5p9pdolft63 is not listed on IDEAS
    3. F. Vergunst & R. E. Tremblay & D. Nagin & Y. Zheng & Cedric Galera & J. Park & E. Beasley & Yann Algan & F. Vitaro & Sylvana M. Cote, 2020. "Inattention in boys from low-income backgrounds predicts welfare receipt: a 30-year prospective study," Post-Print hal-03147221, HAL.
    4. DeZelar, Sharyn & Lightfoot, Elizabeth, 2020. "Who refers parents with intellectual disabilities to the child welfare system? An analysis of referral sources and substantiation," Children and Youth Services Review, Elsevier, vol. 119(C).
    5. Cross, Theodore P. & Tran, Steve P. & Betteridge, Eliza & Hjertquist, Robert & Spinelli, Tawny & Prior, Jennifer & Jordan, Neil, 2021. "The relationship of needs assessed at entry into out-of-home care to children and youth’s later emotional and behavioral problems in care," Children and Youth Services Review, Elsevier, vol. 122(C).
    6. Dembo, Robert S. & Huntington, Nick & Mitra, Monika & Rudolph, Abby E. & Lachman, Margie E. & Mailick, Marsha R., 2022. "Social network typology and health among parents of children with developmental disabilities: Results from a national study of midlife adults," Social Science & Medicine, Elsevier, vol. 292(C).
    7. Tara R. Foti & Carey Watson & Sara R. Adams & Normelena Rios & Mary Staunton & Julia Wei & Stacy A. Sterling & Kathryn K. Ridout & Kelly C. Young-Wolff, 2023. "Associations between Adverse Childhood Experiences (ACEs) and Prenatal Mental Health and Substance Use," IJERPH, MDPI, vol. 20(13), pages 1-13, July.
    8. Shaojie Wei & Chao Zhang & Zhi Geng & Shanshan Luo, 2024. "Identifiability and Estimation for Potential-Outcome Means with Misclassified Outcomes," Mathematics, MDPI, vol. 12(18), pages 1-19, 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:taf:lstaxx:v:46:y:2017:i:14:p:6774-6781. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.