# The Impact of Technical Error of Measurement on Somatotype Categorization
## 4 Discussion
The current study indicates that this type of categorization is the most susceptible to error. Combined with a lack of acknowledgement of TEM, a high chance of mis-categorization may result in less obvious differences between these groups. [PERSON] et al. [20] report TEMs for their skinfolds and other measures of a similar magnitude to the current study, but fail to convert this into somatotype units making it difficult to determine the accuracy of their categorization pattern. If researchers want to accurately determine the exact somatotype grouping of specific sporting populations, it is important that they consider TEM in their data analysis. The current study demonstrated similar TEMs to previous research which assessed the relationship between somatotype and function during exercise [35]. [PERSON] et al. [35] reported their technical error to be less than 0.2 somatotype units (compared to less than 0.1 for the researcher TEM in the current study), and grouped their participants with simple dominance. Accordingly, due to the similar error to the current study, it is postulated that 19 out of the 63 participants were mis-categorized. Despite this they demonstrated a difference in function during exercise between the somatotype groups, with ectomorphs in particular showing different values to those grouped as meso- and endomorphs. Ectomorphs appear to be the least susceptible to mis-categorization via technical error in the current study and so observations in functional differences in this group are likely to be a true representation. In a study with a similar focus, participants were grouped according to dominant somatotype in the more detailed form with 9 endo-mesomorphs, 11 mesomorphs, 12 meso-ectomorphs and 9 ectomorphs following a 12-week endurance training program [36]. However, there is no mention of the magnitude of error within the latter paper. Given that the expertise of the investigator is also not referred to, it is possible that up to 72% of participants (30 of 41) were mis-categorized, leaving the results highly questionable. [PERSON] and [PERSON] [30] also indicated that adolescents of different somatotype categories demonstrated different training responses, yet they did not report their technical error for either individual measures or somatotype as a whole. If participants were miscategorized due to measurement error, their observations may not be as informative. This demonstrates the importance of reporting reliability data when assessing any relationships of somatotype to factors such as training response. The importance of the current study's findings can be contextualized in light of the strengths and weaknesses of the study design. The strong technical skills exercised in the current data set have resulted in low technical error scores. Even then, recognition that some participants may fall slightly outside of their established dominant group is evident, although with low technical error dominance is often still attributed to the originally assigned category. This could be a concern when grouping participants according to dominant somatotype, but is less of a concern when considering the rating as part of a continuum. The population of the current study are from a breadth of somatotype categories, as demonstrated by the SAM of 2.5 being in excess of the 1.0 somatotype unit threshold set by [PERSON] et al. [36] being represented of a large spread of data. This resultsin the error being representative of somatotypes across the spectrum of possible values and categories. Recent research often reports both the protocol (often ISAK) and TEM used [32, 33, 34], demonstrating values that are similar to those seen in the current study. However, despite somatotype being a focus of these studies, they do not report how these errors influence somatotype calculations by reporting somatotype TEM or potential for mis-categorization. Studies that group participants according to somatotype category should take into account measurement error and indicate any potential mis-categorizations.