04 �� R2 < 0.16; moderate if 0.16 �� R2 < 0.49; high if 0.49 �� R2 < 0.81 and; very high if 0.81 �� R2 < 1.0. In addition, it was computed the error of estimation Cabozantinib (s) and the confidence interval for 95% of the adjustment line in the scatter gram. Bland Altman analysis (Bland and Altman, 1986) included the plot of the mean value of TTSA assessed and estimated versus the delta value (i.e., difference) between TTSA assessed and estimated. It was adopted as limits of agreement a bias of �� 1.96 standard deviation of the difference (average difference �� 1.96 standard deviation of the difference). For qualitative assessment it was considered that TTSA estimated was valid and appropriate if at least 80% of the plots were within the �� 1.96 standard deviation of the difference.

Results Morphometric characteristics Tables 1 and and22 present the descriptive statistics for all selected anthropometrical variables in each competitive level sub-sample group. Data dispersion can be considered as ranging from weak (i.e., CV �� 15 %; e.g., H or CP) to moderate (i.e., 15 % < CV �� 30 %; e.g., BM or TTSA) within each sub-sample group. It can be verified that all mean values are higher in male than in female for the expert sub-sample groups, but there were no significant differences based on gender for the non-expert sub-sample groups.

Table 1 Anthropometrical characterization of male (M) and female (F) expert sub-sample groups for the body mass (BM), height (H), biacromial diameter (BCD), chest sagital diameter (CSD), chest perimeter (CP) and measured trunk transverse surface area (TTSA) Table 2 Anthropometrical characterization of male (M) and female (F) non-expert sub-sample groups for the body mass (BM), height (H), biacromial diameter (BCD), chest sagital diameter (CSD), chest perimeter (CP) and measured trunk transverse surface area (TTSA) … Comparing descriptive statistics according to competitive level, it seems that mean values are very close but smoothly higher in the non-expert level sub-sample groups. On the other hand, the CV is higher for the majority of the variables in the expert sub-sample cohorts. Computation of trunk transverse surface area prediction models For male gender, expert sub-sample group, the final model (F2,27 = 6.078; p = 0.01) included the CP (t = 2.307; p = 0.03) and the CSD (t = 1.858; p = 0.08) in order to predict the TTSA.

The equation was (R2 = 0.33; Ra2 = 0.27; s = 165.41; p < 0.01): TTSA=10.505?CP+19.216?CSD?575.496 (5) For male gender, non-expert sub-sample group, the final model (F2,47 = 20.509; p < 0.001) included in the final models the CP (t = 1.050; p = 0.30) and the Anacetrapib CSD (t = 1.606; p = 0.11). The equation was (R2=0.48; Ra2 = 0.45; s = 136.89; p < 0.01): TTSA=5.030?CP+30.453?CSD?371.404 (6) For overall male gender group, including the competitive level as dummy variable (0 = non-expert; 1 = expert), the final model (F3,75 = 17.001; p < 0.001) included the CP (t = 3.253; p < 0.01) and the CSD (t = 2.443; p = 0.