A Primer on the Use of Equivalence Testing for Evaluating Measurement Agreement

dc.contributor.author Dixon, Philip
dc.contributor.author Saint-Maurice, Pedro
dc.contributor.author Kim, Youngwon
dc.contributor.author Dixon, Philip
dc.contributor.author Hibbing, Paul
dc.contributor.author Bai, Yang
dc.contributor.author Welk, Gregory
dc.contributor.department Statistics
dc.contributor.department Kinesiology
dc.date 2019-06-26T01:05:45.000
dc.date.accessioned 2020-07-02T06:56:53Z
dc.date.available 2020-07-02T06:56:53Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.issued 2018-04-01
dc.description.abstract <p>Purpose Statistical equivalence testing is more appropriate than conventional tests of difference to assess the validity of physical activity (PA) measures. This article presents the underlying principles of equivalence testing and gives three examples from PA and fitness assessment research.</p> <p><a href="https://journals.lww.com/acsm-msse/fulltext/2018/04000/A_Primer_on_the_Use_of_Equivalence_Testing_for.25.aspx#HA1-25">Methods </a>The three examples illustrate different uses of equivalence tests. Example 1 uses PA data to evaluate an activity monitor’s equivalence to a known criterion. Example 2 illustrates the equivalence of two field-based measures of physical fitness with no known reference method. Example 3 uses regression to evaluate an activity monitor’s equivalence across a suite of 23 activities.</p> <p>Results The examples illustrate the appropriate reporting and interpretation of results from equivalence tests. In the first example, the mean criterion measure is significantly within ±15% of the mean PA monitor. The mean difference is 0.18 METs and the 90% confidence interval of −0.15 to 0.52 is inside the equivalence region of −0.65 to 0.65. In the second example, we chose to define equivalence for these two measures as a ratio of mean values between 0.98 and 1.02. The estimated ratio of mean V˙O2 values is 0.99, which is significantly (<em>P</em> = 0.007) inside the equivalence region. In the third example, the PA monitor is not equivalent to the criterion across the suite of activities. The estimated regression intercept and slope are −1.23 and 1.06. Neither confidence interval is within the suggested regression equivalence regions.</p> <p>Conclusions When the study goal is to show similarity between methods, equivalence testing is more appropriate than traditional statistical tests of differences (e.g., ANOVA and <em>t</em>-tests).</p>
dc.description.comments <p>This article is published as Dixon, P.M., Saint-Maurice, P.F., Kim, Y., Hibbing, P., Bai, Y. and Welk, G.J. 2018. A primer on the use of equivalence testing for evaluating measurement agreement. <em>Medicine & Science in Sports & Exercise</em> 50:837-845. doi: <a href="http://dx.doi.org/10.1249/MSS.0000000000001481" target="_blank">10.1249/MSS.0000000000001481</a>. </p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/stat_las_pubs/160/
dc.identifier.articleid 1164
dc.identifier.contextkey 14403569
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_pubs/160
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/90466
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_pubs/160/2018_Dixon_PrimerUse.pdf|||Fri Jan 14 20:53:42 UTC 2022
dc.source.uri 10.1249/MSS.0000000000001481
dc.subject.disciplines Exercise Science
dc.subject.disciplines Kinesiology
dc.subject.disciplines Statistical Methodology
dc.subject.keywords calibration
dc.subject.keywords validation
dc.subject.keywords criterion validity
dc.subject.keywords convergent validity
dc.title A Primer on the Use of Equivalence Testing for Evaluating Measurement Agreement
dc.type article
dc.type.genre article
dspace.entity.type Publication
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