2004
DOI: 10.2310/6640.2004.15377
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Getting More from the Literature: Estimating the Standard Error of Measurement from Reliability Studies

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Cited by 259 publications
(160 citation statements)
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“…We calculated coefficients of variation (CVs) for the 6MWT and 10mWT between day 1 and day 2 to examine within-subject variability. SEM was calculated for the SAM using the formula s (1 -r) -1 , where s = SD of the test and r = reliability coefficient of the test [25][26].…”
Section: Resultsmentioning
confidence: 99%
“…We calculated coefficients of variation (CVs) for the 6MWT and 10mWT between day 1 and day 2 to examine within-subject variability. SEM was calculated for the SAM using the formula s (1 -r) -1 , where s = SD of the test and r = reliability coefficient of the test [25][26].…”
Section: Resultsmentioning
confidence: 99%
“…a statistical estimate of the smallest detectable change corresponding to change in ability) [41,42]. These cannot be calculated from Evaluation of Daily Activity Questionnaire domain scores which are summed from ordinal data [43].…”
Section: Statistical Analysesmentioning
confidence: 99%
“…According to Beckerman et al (2001) and Stratford (2004), the SEM represents the within-subject reliability of the measure and, consequently, the reliability of the measure (Beckerman et al, 2001;Stratford, 2004). The SEM was determined using the following formula: SEM = √MSE, where MSE = mean square error.…”
Section: Reliability Analysesmentioning
confidence: 99%