IDEAS home Printed from https://ideas.repec.org/a/bpj/ijbist/v7y2011i1n9.html
   My bibliography  Save this article

An Improved Bland-Altman Method for Concordance Assessment

Author

Listed:
  • Liao Jason J. Z.
  • Capen Robert

Abstract

It is often necessary to compare two measurement methods in medicine and other experimental sciences. This problem covers a broad range of data with applications arising from many different fields. The Bland-Altman method has been a favorite method for concordance assessment. However, the Bland-Altman approach creates a problem of interpretation for many applications when a mixture of fixed bias, proportional bias and/or proportional error occurs. In this paper, an improved Bland-Altman method is proposed to handle more complicated scenarios in practice. This new approach includes Bland-Altman's approach as its special case. We evaluate concordance by defining an agreement interval for each individual paired observation and assessing the overall concordance. The proposed interval approach is very informative and offers many advantages over existing approaches. Data sets are used to demonstrate the advantages of the new method.

Suggested Citation

  • Liao Jason J. Z. & Capen Robert, 2011. "An Improved Bland-Altman Method for Concordance Assessment," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-17, January.
    • Handle: RePEc:bpj:ijbist:v:7:y:2011:i:1:n:9
    DOI: 10.2202/1557-4679.1295
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1557-4679.1295
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1557-4679.1295?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. Carstensen Bendix & Simpson Julie & Gurrin Lyle C, 2008. "Statistical Models for Assessing Agreement in Method Comparison Studies with Replicate Measurements," The International Journal of Biostatistics, De Gruyter, vol. 4(1), pages 1-28, July.
    2. Lin L. & Hedayat A. S. & Sinha B. & Yang M., 2002. "Statistical Methods in Assessing Agreement: Models, Issues, and Tools," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 257-270, March.
    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. Liao Jason J. Z., 2015. "Quantifying an Agreement Study," The International Journal of Biostatistics, De Gruyter, vol. 11(1), pages 125-133, May.

    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. Jose M. Jimenez-Olmedo & Alfonso Penichet-Tomas & Basilio Pueo & Lamberto Villalon-Gasch, 2023. "Reliability of ADR Jumping Photocell: Comparison of Beam Cut at Forefoot and Midfoot," IJERPH, MDPI, vol. 20(11), pages 1-13, May.
    2. Hutson, Alan D., 2010. "A multi-rater nonparametric test of agreement and corresponding agreement plot," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 109-119, January.
    3. Masha Kocherginsky & Megan Huisingh-Scheetz & William Dale & Diane S Lauderdale & Linda Waite, 2017. "Measuring Physical Activity with Hip Accelerometry among U.S. Older Adults: How Many Days Are Enough?," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-13, January.
    4. Correndo, Adrian A. & Hefley, Trevor J. & Holzworth, Dean P. & Ciampitti, Ignacio A., 2021. "Revisiting linear regression to test agreement in continuous predicted-observed datasets," Agricultural Systems, Elsevier, vol. 192(C).
    5. Richard A Parker & Christopher J Weir & Noah Rubio & Roberto Rabinovich & Hilary Pinnock & Janet Hanley & Lucy McCloughan & Ellen M Drost & Leandro C Mantoani & William MacNee & Brian McKinstry, 2016. "Application of Mixed Effects Limits of Agreement in the Presence of Multiple Sources of Variability: Exemplar from the Comparison of Several Devices to Measure Respiratory Rate in COPD Patients," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-15, December.
    6. Choudhary, Pankaj K., 2007. "Semiparametric regression for assessing agreement using tolerance bands," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6229-6241, August.
    7. Choudhary Pankaj K, 2010. "A Unified Approach for Nonparametric Evaluation of Agreement in Method Comparison Studies," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-26, June.
    8. Chen, Chia-Cheng & Barnhart, Huiman X., 2008. "Comparison of ICC and CCC for assessing agreement for data without and with replications," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 554-564, December.
    9. Jordan A. Carlson & Bo Liu & James F. Sallis & Jacqueline Kerr & J. Aaron Hipp & Vincent S. Staggs & Amy Papa & Kelsey Dean & Nuno M. Vasconcelos, 2017. "Automated Ecological Assessment of Physical Activity: Advancing Direct Observation," IJERPH, MDPI, vol. 14(12), pages 1-15, December.
    10. Dejian Lai & Shyang-Yun Pamela Shiao, 2005. "Comparing two clinical measurements: a linear mixed model approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(8), pages 855-860.
    11. Kerryn A Moore & Julie A Simpson & Kyla H Thomas & Marcus J Rijken & Lisa J White & Saw Lu Moo Dwell & Moo Kho Paw & Jacher Wiladphaingern & Sasithon Pukrittayakamee & François Nosten & Freya J I Fowk, 2015. "Estimating Gestational Age in Late Presenters to Antenatal Care in a Resource-Limited Setting on the Thai-Myanmar Border," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-17, June.
    12. Li, Runze & Chow, Mosuk, 2005. "Evaluation of reproducibility for paired functional data," Journal of Multivariate Analysis, Elsevier, vol. 93(1), pages 81-101, March.
    13. Wei, Bo & Dai, Tian & Peng, Limin & Guo, Ying & Manatunga, Amita, 2020. "A new functional representation of broad sense agreement," Statistics & Probability Letters, Elsevier, vol. 158(C).
    14. Gao, Jingjing & Pan, Yi & Haber, Michael, 2012. "Assessment of observer agreement for matched repeated binary measurements," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1052-1060.
    15. Lisa R. Goldberg & Saad Mouti, 2019. "Sustainable Investing and the Cross-Section of Returns and Maximum Drawdown," Papers 1905.05237, arXiv.org, revised Dec 2023.

    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:ijbist:v:7:y:2011:i:1:n:9. 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.