IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v60y2013icp132-145.html
   My bibliography  Save this article

Assessing agreement with intraclass correlation coefficient and concordance correlation coefficient for data with repeated measures

Author

Listed:
  • Chen, Chia-Cheng
  • Barnhart, Huiman X.

Abstract

The intraclass correlation coefficient and the concordance correlation coefficient are two popular scaled indices for assessing the closeness between observers who make measurements for quantitative responses. These two indices are usually based on subject and observer effects only, and therefore we cannot use these indices if the observer produces repeated measurements rather than replicated readings. In this paper, we consider not only subject and observer effects, but also time effects for data with repeated measurements since it is difficult to obtain the true replications in practice. We compare these two agreement indices for different combinations of random or fixed effects of observer and time. Finally, we use image data of 2D-echocardiograms to illustrate the proposed methodology and the comparison of these two indices. If there is a need to choose between these two indices for repeated measurements, we recommend to use the new concordance correlation coefficient since it does not need ANOVA assumptions.

Suggested Citation

  • Chen, Chia-Cheng & Barnhart, Huiman X., 2013. "Assessing agreement with intraclass correlation coefficient and concordance correlation coefficient for data with repeated measures," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 132-145.
    • Handle: RePEc:eee:csdana:v:60:y:2013:i:c:p:132-145
    DOI: 10.1016/j.csda.2012.11.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947312003957
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2012.11.004?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. 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.
    2. Tony Vangeneugden & Annouschka Laenen & Helena Geys & Didier Renard & Geert Molenberghs, 2005. "Applying Concepts of Generalizability Theory on Clinical Trial Data to Investigate Sources of Variation and Their Impact on Reliability," Biometrics, The International Biometric Society, vol. 61(1), pages 295-304, 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. Thiago de Paula Oliveira & John Hinde & Silvio Sandoval Zocchi, 2018. "Longitudinal Concordance Correlation Function Based on Variance Components: An Application in Fruit Color Analysis," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(2), pages 233-254, June.
    2. Cacciotti, Gabriella & Hayton, James C. & Mitchell, J. Robert & Allen, David G., 2020. "Entrepreneurial fear of failure: Scale development and validation," Journal of Business Venturing, Elsevier, vol. 35(5).

    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. Tony Vangeneugden & Geert Molenberghs & Geert Verbeke & Clarice G.B. Dem�trio, 2011. "Marginal correlation from an extended random-effects model for repeated and overdispersed counts," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 215-232, September.
    2. Matheus Pereira Libório & Lívia Maria Leite Silva & Petr Iakovlevitch Ekel & Letícia Ribeiro Figueiredo & Patrícia Bernardes, 2022. "Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1073-1099, December.
    3. Masatoshi Teraguchi & Dino Samartzis & Hiroshi Hashizume & Hiroshi Yamada & Shigeyuki Muraki & Hiroyuki Oka & Jason Pui Yin Cheung & Ryohei Kagotani & Hiroki Iwahashi & Sakae Tanaka & Hiroshi Kawaguch, 2016. "Classification of High Intensity Zones of the Lumbar Spine and Their Association with Other Spinal MRI Phenotypes: The Wakayama Spine Study," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-15, September.
    4. 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.
    5. Candelaria de la Merced Díaz‐González & Milagros de la Rosa‐Hormiga & Josefa M. Ramal‐López & Juan José González‐Henríquez & María Sandra Marrero‐Morales, 2018. "Factors which influence concordance among measurements obtained by different pulse oximeters currently used in some clinical situations," Journal of Clinical Nursing, John Wiley & Sons, vol. 27(3-4), pages 677-683, February.

    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:csdana:v:60:y:2013:i:c:p:132-145. 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: http://www.elsevier.com/locate/csda .

    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.