# Criterion-Related Validity and Reliability of the Front Plank Test in Adults: The ADULT-FIT Project
## 2 Materials and Methods
### Statistical Analyses
#### 2.4.2 Reliability  
The relative reliability of the field FPT was investigated through a t-test and intraclass correlation coefficient (ICC). Following [PERSON] et al. (2009), we classified the magnitude of the values of the ICC through a qualitative scale: values close to 0.1 are considered low reliability; 0.3, moderate; 0.5, high; 0.7, very high; and those close to 0.9, extremely high [40]. We also examined the differences between test and retest (hereafter called T1 and T2) using different error measures. Generally, the lower the error value, the lower the dispersion between T1 and T2 measurements. The sum of squared errors (SSE) was calculated as follows: SSE = \(\sum_{i=1}^{N}(yi-\hat{y})^{2}\), where \(n\) is the cases to evaluate the error measurements, \(\hat{y}\) is the T2, and \(y\) is the T1. The mean sum of squared errors (MSE): MSE = \(\frac{1}{N}\sum_{i=1}^{N}(yi-\hat{y})^{2}\). The root mean sum of squared errors (RMSE) was calculated by converting MSE into domain units by taking the root square: RMSE = \(\sqrt{MSE}\). The percentage error was calculated as follows: \(\%\)Error = \(\frac{RMSE}{y_{max}-y_{min}}\times 100\).  
The following methods were used to study absolute reliability: standard error of measurement (SEM) as a percentage of the mean value of the measurements, standard error of estimate (SEE), the coefficient of variation (CV), and Bland-Altman plots [41; 42], whose  
Figure 2: Exercises performed for maximal voluntary isometric contraction of (**A**) upper and lower rectus abdominis, (**B**) external oblique, and (**C**) erect spinae and multifidus.  
difference was calculated using an ANOVA test for repeated measures. These measures were calculated as follows: %SEM = mean of the difference scores between 2 trials \(\times\) 100/mean of the first trial, with a value of SEM \(\leq\) 15% considered acceptable [43]; SEE = \(SD\hat{y}\sqrt{(1-R^{2}y\hat{y})}\); CV = \(\frac{\delta}{X}\times\) 100, with a CV \(\leq\) 10% considered acceptable [44]. In addition, the CV method provides useful information in the presence of heteroscedasticity (assumes that the greatest T1 and T2 variation occurs in individuals scoring the highest values in the test). Heteroscedasticity of errors was also identified in the Bland-Altman plots and was defined as a coefficient of determination (\(r^{2}\)) \(>\) 0.1. To estimate the smallest change in score that indicates a \"real change\" in 90% of participants, the minimal detectable change (MDC\({}_{90}\)) [45] was calculated; MDC\({}_{90}\) = SEM \(\times\sqrt{2}\times\) 1.65.  
Finally, [PERSON]'s \(d\) was computed to quantify the magnitude of the difference between T1 and T2. The scale used for interpreting the magnitude of the ES was specific to training research: negligible (\(<\)0.2), small (0.2-0.5), medium (0.5-0.8), and large (\(\geq\)0.8) [46]. The analyses were conducted for the whole sample, and separately by sex and age for all criterion-related and reliability analyses. All the analyses were performed using the Statistical Package for Social Sciences (IBM SPSS Statistics for Windows, version 26.0; Armonk, NY, USA) and the level of significance was set at \(p\)\(<\) 0.05.