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Estimated effect sizes, measurement variability, and correlations between baseline and follow-up measures were estimated using unpublished datasets from studies of physiologic measures in adult and pediatric populations.
All efficiency measures were estimated using the DEAP 2.1 program created by Coelli (1996a).
The confidence intervals for these measures were estimated using bootstrap.
Standard errors (SEboot) of evaluation measures were estimated using a bootstrapping method with 1000 replicates.
Correlations between hormonal data and anthropometrics measures were estimated using Pearson's correlation coefficient.
Correlations between measures were estimated using Pearson's correlation coefficient and tested for significance using a two-sided t-test test.
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10 11 The interobserver reliability for these measures was estimated using Cronbach's α.
The effect of the independent variables on the dichotomous outcome measures was estimated using logistic regression models.
To test reliability, the internal consistency for summary measures was estimated using Cronbachs' alpha coefficient and alpha equal to or greater than 0.70 was considered satisfactory [ 30].
To test reliability, the internal consistency for summary measures was estimated using Cronbach's alpha coefficient and alpha equal to or greater than 0.70 was considered satisfactory [ 25].
The continuous ACR response underlying the binary ACR 20, ACR 50 and ACR 70 measures is estimated using the mean ACRcont response for each of the four responder groups.
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