## 3 Results and Discussion
### OWHTO Geometric Planning Optimization
In order to observe whether the models presented in Table 4 are relevant, in the next step the correlation coefficient (R\({}^{2}\)) and the adjusted correlation coefficient (R\({}^{2}\) adj) were established. The values of these coefficients suggest whether the model provides a satisfactory representation of the process. Thus, for a model to be satisfactory for a process, R\({}^{2}\) and R\({}^{2}\) adj must be at least 0.80. The values obtained for R\({}^{2}\) and R\({}^{2}\) adj, respectively, for the three models in Table 4 are presented in Table 5.  
The results presented in Table 5 show that both the correlation coefficient (R\({}^{2}\)) and the adjusted correlation coefficient (R\({}^{2}\) adj) have values much higher than 0.8, very close \begin{table}
\begin{tabular}{l c} \hline \hline \multicolumn{1}{c}{**Parameters**} & \multicolumn{1}{c}{**Regression Equation**} \\ \hline Equivalent stress & Equivalent stress = 336.1 + 1.341 V1 \(-\) 32.20 V2 + 1.844 V3 + 0.785 V4 \\ \hline Shear stress & Shear stress = 184.4 + 0.608 V1 \(-\) 17.218 V2 + 0.950 V3 + 0.313 V4 \\ \hline Displacement & Displacement = 2.413 + 0.01350 V1 \(-\) 0.2740 V2 + 0.02300 V3 + 0.00583 V4 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Regression equations for: equivalent stress, shear stress, displacement. Figure 11: Static FEM analysis for model with code 6: (**a**)—equivalent stress, (**b**)—shear stress, (**c**)—displacement. Figure 12: Static FEM analysis for model with code 7: (**a**)—equivalent stress, (**b**)—shear stress, (**c**)—displacement. to 1, which demonstrates that the models in the equations of regression have a very good representation of the process. Additionally, in order to observe if the models represented by the regression equations are significant, the values of F and p were calculated. If the value of F is high, it suggests that the model is significant, and if the value of p is less than 0.05, the model is significant. The values calculated for F and p are shown in Table 6.  
The analysis of the respective values of F and p presented in Table 6 show that F has high enough values and p has low enough values for the models given by the regression equations and the meaning of their terms to be significant. However, the displacement model is less significant compared to the other two, but it is still significant enough considering the values of F and p. It is also very important to know the influence that each of the four variables has on the three parameters and, thus, a response for signal to noise ratios (smaller is better) was established, see Table 7, but a multiple regression analysis was also performed, which allowed the values for V1,b*,V2,b*,V3,b*,V4,b* to be established, see Table 8.  
From the analysis of the data presented in Tables 7 and 8, respectively, it could be observed that, both after establishing the response for signal to noise ratios and after establishing the values for V1,b*,V2,b*,V3,b*,V4,b*, the same ranking of the influence of the four variables was obtained (V1, V2, V3, V4). Thus, the variable V2 has the greatest influence, which demonstrates that, in practice, it is very important to pay special attention to the positioning of the CORA in relation to the lateral cortex of the bone. It is also worth noting that the influence of the correction angle has a small influence on the stresses and strains in the CORA compared to the other parameters and highlights the importance of the geometric planning of the OWHTO. It is worth noting the usefulness of the computer-aided approach to CAD-CAM methods of medical aspects through the superior possibilities of processing the results obtained on virtual models. Such biomechanical approaches are present in the literature [41; 42]. \begin{table}
\begin{tabular}{l c c} \hline \hline
**Parameter Regression Equations** & **F** & **p** \\ \hline Equivalent stress & 138.6078 & 0.000984 \\ \hline Shear stress & 122.9075 & 0.001177 \\ \hline Displacement & 74.17242 & 0.0026 \\ \hline \hline \end{tabular}
\end{table}