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

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...

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Main Authors: Sharmila Vaz, Torbjörn Falkmer, Anne Elizabeth Passmore, Richard Parsons, Pantelis Andreou
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3767825?pdf=render
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spelling doaj-4d206fb9719d4140a2ab8929d7409c622020-11-25T02:22:53ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0189e7399010.1371/journal.pone.0073990The case for using the repeatability coefficient when calculating test-retest reliability.Sharmila VazTorbjörn FalkmerAnne Elizabeth PassmoreRichard ParsonsPantelis AndreouThe 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.http://europepmc.org/articles/PMC3767825?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Sharmila Vaz
Torbjörn Falkmer
Anne Elizabeth Passmore
Richard Parsons
Pantelis Andreou
spellingShingle Sharmila Vaz
Torbjörn Falkmer
Anne Elizabeth Passmore
Richard Parsons
Pantelis Andreou
The case for using the repeatability coefficient when calculating test-retest reliability.
PLoS ONE
author_facet Sharmila Vaz
Torbjörn Falkmer
Anne Elizabeth Passmore
Richard Parsons
Pantelis Andreou
author_sort Sharmila Vaz
title The case for using the repeatability coefficient when calculating test-retest reliability.
title_short The case for using the repeatability coefficient when calculating test-retest reliability.
title_full The case for using the repeatability coefficient when calculating test-retest reliability.
title_fullStr The case for using the repeatability coefficient when calculating test-retest reliability.
title_full_unstemmed The case for using the repeatability coefficient when calculating test-retest reliability.
title_sort case for using the repeatability coefficient when calculating test-retest reliability.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description 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.
url http://europepmc.org/articles/PMC3767825?pdf=render
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