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    The case for using the repeatability coefficient when calculating test-retest reliability

    194751_95812_The_Case_for_Using_the_Repeatability_Coefficient_....pdf (272.9Kb)
    Access Status
    Open access
    Authors
    Vaz, Sharmila
    Falkmer, Torbjorn
    Passmore, Anne
    Parsons, Richard
    Andreou, P.
    Date
    2013
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Vaz, Sharmila and Falkmer, Torbjorn and Passmore, Anne Elizabeth and Parsons, Richard and Andreou, Pantelis. 2013. The case for using the repeatability coefficient when calculating test-retest reliability. PLoS ONE. 8 (9): e73990.
    Source Title
    PLoS ONE
    DOI
    10.1371/journal.pone.0073990
    ISSN
    19326203
    Remarks

    This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/. Please refer to the licence to obtain terms for any further reuse or distribution of this work.

    URI
    http://hdl.handle.net/20.500.11937/16638
    Collection
    • Curtin Research Publications
    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.

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