## 4 Results
### Results of Analyses Investigating the Effects of Three Factors
#### 4.3.1 Analysis of the Triplet Camera Type, Rotation and Contrast Ratio  
The first triplet to be examined was the camera type, camera rotation and the contrast ratio. The authors used the same rotation and contrast ratio groups as before. The numerical results of these groups as defined by the triplets are presented in Table 15, and the results of the logistic regression analysis are presented in Table 28. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Contrast Ratio and Device Used** & **Estimate** & **Standard Error** & \(z\)**Value** & **Pr (\textgreater{}|z|)** \\ \hline Intercept & 0.65115 & 0.01679 & 38.786 & \textless{}2 \(\times\) 10\({}^{-16}\) \\ INC\_C & 0.08647 & 0.02514 & 3.440 & 0.000583 \\ Gear VR & 0.03204 & 0.03780 & 0.848 & 0.396699 \\ INC\_C and Gear VR & 0.09445 & 0.05644 & 1.674 & 0.094199 \\ \hline \hline \end{tabular}
\end{table} 
Table 26: Logistic regression analysis results of the additive model with variables contrast ratio and device used allowing interactions. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Resid.** & **Df Resid.** & **Dev** & **Df** & **Deviance** & **Pr (\textgreater{}Chi)** \\ \hline
1 & 2706 & 10,128 & - & - & - \\
2 & 2705 & 10,125 & 1 & 2.804 & 0.09403 \\ \hline \hline \end{tabular}
\end{table} 
Table 27: Comparison of the variables contrast ratio and device used by ANOVA. The reference point was \"Orthographic, NO_R, NO_C\". As can be seen, the values of \"Orthographic, INC_R, INC_C\" and the values of all Perspective values are significantly better than \"Orthographic, NO_R, NO_C\". The authors checked and concluded that the \"Orthographic, INC_R, INC_C\" and the Perspective rows could not be distinguished from one another. With the ANOVA dispersion analysis method, a comparison was made between the logistic regression models with additive property without interactions (I), the models with interactions between two variables (II), and the models allowing interactions among all three variables (III). When comparing I and II, the model took into account the interactions of the camera type and camera rotation, moreover the interaction of camera type and contrast ratio gave significantly better results than the logistic regression models without interactions (\(p\)-value = 0.001258). The interaction of camera rotation and contrast ratio was not significant, as was presented in the previous section; therefore, the authors omitted it in this section. The case is the same when comparing I and III (\(p\)-value = 0.002387). However, when comparing II and III, it can be concluded that the model in which interaction of all three variables is built in does not give better results than model II (\(p\)-value = 0.2049). The results of the ANOVA can be seen in Table 29.  
Therefore, the authors present the results of the logistic regression analysis in the case of the most appropriate model, which is model II. In Table 30, the effects of the factors according to model II can be seen. This means that every variable has an influence, and the interaction in case of camera type and contrast ratio is significant. To double-check ourselves, and the results as well, the authors compared \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Camera Type, Rotation and Contrast Ratio** & **Estimate** & **Standard Error** & \(z\)**Value** & **Pr (\textgreater{}|z|)** \\ \hline Intercept & 0.5062478 & 0.0238618 & 21.216 & \(<\)\(2\times 10^{-16}\) \\ Perspective & 0.2259740 & 0.0344853 & 6.553 & \(5.65\times 10^{-11}\) \\ INC\_R & 0.1054279 & 0.0388003 & 2.717 & 0.006584 \\ INC\_C & 0.1378076 & 0.0389859 & 3.535 & 0.000408 \\ Perspective and INC\_R & 0.0006636 & 0.0528045 & 0.013 & 0.989973 \\ Perspective and INC\_C & \(-\)0.1653400 & 0.0528044 & \(-\)3.131 & 0.001741 \\ \hline \hline \end{tabular}
\end{table} 
Table 30: Logistic regression analysis results of the additive model using variables camera type, rotation and the contrast ratio and allowing interactions of two variables.