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      Design and Implementation of an Integrated Performance Monitoring Tool for Swimming to Extract Stroke Information at Real Time

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          Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM.

          Reliability, the consistency of a test or measurement, is frequently quantified in the movement sciences literature. A common metric is the intraclass correlation coefficient (ICC). In addition, the SEM, which can be calculated from the ICC, is also frequently reported in reliability studies. However, there are several versions of the ICC, and confusion exists in the movement sciences regarding which ICC to use. Further, the utility of the SEM is not fully appreciated. In this review, the basics of classic reliability theory are addressed in the context of choosing and interpreting an ICC. The primary distinction between ICC equations is argued to be one concerning the inclusion (equations 2,1 and 2,k) or exclusion (equations 3,1 and 3,k) of systematic error in the denominator of the ICC equation. Inferential tests of mean differences, which are performed in the process of deriving the necessary variance components for the calculation of ICC values, are useful to determine if systematic error is present. If so, the measurement schedule should be modified (removing trials where learning and/or fatigue effects are present) to remove systematic error, and ICC equations that only consider random error may be safely used. The use of ICC values is discussed in the context of estimating the effects of measurement error on sample size, statistical power, and correlation attenuation. Finally, calculation and application of the SEM are discussed. It is shown how the SEM and its variants can be used to construct confidence intervals for individual scores and to determine the minimal difference needed to be exhibited for one to be confident that a true change in performance of an individual has occurred.
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            A Meta-Analysis of Cronbach's Coefficient Alpha

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              The 4+1 View Model of architecture

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                Author and article information

                Journal
                IEEE Transactions on Human-Machine Systems
                IEEE Trans. Human-Mach. Syst.
                Institute of Electrical and Electronics Engineers (IEEE)
                2168-2291
                2168-2305
                March 2013
                March 2013
                : 43
                : 2
                : 199-213
                Article
                10.1109/TSMC.2012.2235428
                c1d042cf-9f06-4c3b-a9ed-229145b5b4ae
                © 2013
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