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The Case for Using the Repeatability Coefficient When Calculating Test–Retest Reliability

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  • Sharmila Vaz
  • Torbjörn Falkmer
  • Anne Elizabeth Passmore
  • Richard Parsons
  • Pantelis Andreou

Abstract

The use of standardised tools is an essential component of evidence-based practice. Reliance on standardised tools places demands on clinicians to understand their properties, strengths, and weaknesses, in order to interpret results and make clinical decisions. This paper makes a case for clinicians to consider measurement error (ME) indices Coefficient of Repeatability (CR) or the Smallest Real Difference (SRD) over relative reliability coefficients like the Pearson’s (r) and the Intraclass Correlation Coefficient (ICC), while selecting tools to measure change and inferring change as true. The authors present statistical methods that are part of the current approach to evaluate test–retest reliability of assessment tools and outcome measurements. Selected examples from a previous test–retest study are used to elucidate the added advantages of knowledge of the ME of an assessment tool in clinical decision making. The CR is computed in the same units as the assessment tool and sets the boundary of the minimal detectable true change that can be measured by the tool.

Suggested Citation

  • Sharmila Vaz & Torbjörn Falkmer & Anne Elizabeth Passmore & Richard Parsons & Pantelis Andreou, 2013. "The Case for Using the Repeatability Coefficient When Calculating Test–Retest Reliability," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
    • Handle: RePEc:plo:pone00:0073990
    DOI: 10.1371/journal.pone.0073990
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    Cited by:

    1. Emma von Wowern & Gerd Östling & Peter M Nilsson & Per Olofsson, 2015. "Digital Photoplethysmography for Assessment of Arterial Stiffness: Repeatability and Comparison with Applanation Tonometry," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-19, August.
    2. Hayfa Almutary & Nahla Tayyib, 2021. "Translation, Adaptation, and Validation of Chronic Kidney Disease Self-Management and Knowledge Instruments for People at Pre-Dialysis Stage in the Arab World," Clinical Nursing Research, , vol. 30(8), pages 1231-1240, November.
    3. Jan Henrik Terheyden & Maximilian W M Wintergerst & Peyman Falahat & Moritz Berger & Frank G Holz & Robert P Finger, 2020. "Automated thresholding algorithms outperform manual thresholding in macular optical coherence tomography angiography image analysis," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-12, March.
    4. Beatrice Backman Lönn & Niclas Olofsson & Mats Jong, 2019. "Translation and validation of the Clinical Trial Nursing Questionnaire in Swedish—A first step to clarify the clinical research nurse role in Sweden," Journal of Clinical Nursing, John Wiley & Sons, vol. 28(13-14), pages 2696-2705, July.

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