IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v10y2011i1n35.html
   My bibliography  Save this article

Measurement of Evidence and Evidence of Measurement

Author

Listed:
  • Vieland Veronica J
  • Hodge Susan E

Abstract

One important use of statistical methods in application to biological data is measurement of evidence, or assessment of the degree to which data support one or another hypothesis. While there is a small literature on this topic, it seems safe to say that consensus has not yet been reached regarding how best, or most accurately, to measure statistical evidence. Here, we propose considering the problem as a measurement problem, rather than as a statistical problem per se, and we explore the consequences of this shift in perspective. Our arguments here are part of an ongoing research program focused on exploiting deep parallelisms between foundations of thermodynamics and foundations of “evidentialism,” in order to derive an absolute scale for the measurement of evidence, a general framework in the context of which that scale is validated, and the many ancillary benefits that come from having such a framework in place.

Suggested Citation

  • Vieland Veronica J & Hodge Susan E, 2011. "Measurement of Evidence and Evidence of Measurement," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-11, July.
  • Handle: RePEc:bpj:sagmbi:v:10:y:2011:i:1:n:35
    DOI: 10.2202/1544-6115.1682
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1544-6115.1682
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.2202/1544-6115.1682?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. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Kimberly A Walters & Yungui Huang & Marco Azaro & Kathleen Tobin & Thomas Lehner & Linda M Brzustowicz & Veronica J Vieland, 2014. "Meta-Analysis of Repository Data: Impact of Data Regularization on NIMH Schizophrenia Linkage Results," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-8, January.
    2. Veronica J Vieland & Sang-Cheol Seok, 2021. "The PPLD has advantages over conventional regression methods in application to moderately sized genome-wide association studies," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-22, September.

    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. Alexander Frankel & Maximilian Kasy, 2022. "Which Findings Should Be Published?," American Economic Journal: Microeconomics, American Economic Association, vol. 14(1), pages 1-38, February.
    2. Jyotirmoy Sarkar, 2018. "Will P†Value Triumph over Abuses and Attacks?," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 7(4), pages 66-71, July.
    3. Stanley, T. D. & Doucouliagos, Chris, 2019. "Practical Significance, Meta-Analysis and the Credibility of Economics," IZA Discussion Papers 12458, Institute of Labor Economics (IZA).
    4. Karin Langenkamp & Bodo Rödel & Kerstin Taufenbach & Meike Weiland, 2018. "Open Access in Vocational Education and Training Research," Publications, MDPI, vol. 6(3), pages 1-12, July.
    5. Kevin J. Boyle & Mark Morrison & Darla Hatton MacDonald & Roderick Duncan & John Rose, 2016. "Investigating Internet and Mail Implementation of Stated-Preference Surveys While Controlling for Differences in Sample Frames," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(3), pages 401-419, July.
    6. Jelte M Wicherts & Marjan Bakker & Dylan Molenaar, 2011. "Willingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-7, November.
    7. Valentine, Kathrene D & Buchanan, Erin Michelle & Scofield, John E. & Beauchamp, Marshall T., 2017. "Beyond p-values: Utilizing Multiple Estimates to Evaluate Evidence," OSF Preprints 9hp7y, Center for Open Science.
    8. Anton, Roman, 2014. "Sustainable Intrapreneurship - The GSI Concept and Strategy - Unfolding Competitive Advantage via Fair Entrepreneurship," MPRA Paper 69713, University Library of Munich, Germany, revised 01 Feb 2015.
    9. Dudek, Thomas & Brenøe, Anne Ardila & Feld, Jan & Rohrer, Julia, 2022. "No Evidence That Siblings' Gender Affects Personality across Nine Countries," IZA Discussion Papers 15137, Institute of Labor Economics (IZA).
    10. Uwe Hassler & Marc‐Oliver Pohle, 2022. "Unlucky Number 13? Manipulating Evidence Subject to Snooping," International Statistical Review, International Statistical Institute, vol. 90(2), pages 397-410, August.
    11. Frederique Bordignon, 2020. "Self-correction of science: a comparative study of negative citations and post-publication peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1225-1239, August.
    12. Omar Al-Ubaydli & John A. List, 2015. "Do Natural Field Experiments Afford Researchers More or Less Control than Laboratory Experiments? A Simple Model," NBER Working Papers 20877, National Bureau of Economic Research, Inc.
    13. Aurelie Seguin & Wolfgang Forstmeier, 2012. "No Band Color Effects on Male Courtship Rate or Body Mass in the Zebra Finch: Four Experiments and a Meta-Analysis," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-11, June.
    14. Ankur Moitra & Dhruv Rohatgi, 2022. "Provably Auditing Ordinary Least Squares in Low Dimensions," Papers 2205.14284, arXiv.org, revised Jun 2022.
    15. Dragana Radicic & Geoffrey Pugh & Hugo Hollanders & René Wintjes & Jon Fairburn, 2016. "The impact of innovation support programs on small and medium enterprises innovation in traditional manufacturing industries: An evaluation for seven European Union regions," Environment and Planning C, , vol. 34(8), pages 1425-1452, December.
    16. Colin F. Camerer & Anna Dreber & Felix Holzmeister & Teck-Hua Ho & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Gideon Nave & Brian A. Nosek & Thomas Pfeiffer & Adam Altmejd & Nick Buttrick , 2018. "Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015," Nature Human Behaviour, Nature, vol. 2(9), pages 637-644, September.
    17. Li, Lunzheng & Maniadis, Zacharias & Sedikides, Constantine, 2021. "Anchoring in Economics: A Meta-Analysis of Studies on Willingness-To-Pay and Willingness-To-Accept," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
    18. Eric van Diessen & Willemiek J E M Zweiphenning & Floor E Jansen & Cornelis J Stam & Kees P J Braun & Willem M Otte, 2014. "Brain Network Organization in Focal Epilepsy: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-21, December.
    19. Charles F. Manski, 2018. "Reasonable patient care under uncertainty," Health Economics, John Wiley & Sons, Ltd., vol. 27(10), pages 1397-1421, October.
    20. Kathryn Oliver & Annette Boaz, 2019. "Transforming evidence for policy and practice: creating space for new conversations," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-10, December.

    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:bpj:sagmbi:v:10:y:2011:i:1:n:35. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.