## 3 Results
### Analysis of Success
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & & \multicolumn{3}{c}{**Image**} \\ \cline{3-5}  & & \multicolumn{1}{c}{**Achromatic**} & **Colored** & **Total** \\ \hline \multirow{4}{*}{Success} & \multirow{2}{*}{Failed} & Count & 77 & 218 & 295 \\ \cline{3-5}  & & \% within success & & \\ \cline{2-5}  & & Count & 285 & 498 & 783 \\ \cline{2-5}  & & \% within success & 36.4\% & 63.6\% & 100.0\% \\ \hline \multirow{4}{*}{Total} & Count & 362 & 716 & 1078 \\ \cline{2-5}  & & \% within success & 33.6\% & 66.4\% & 100.0\% \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Cross-tabulation of success \(\times\) image parameters. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Parameters**} & \multirow{2}{*}{**Coefficient**} & \multirow{2}{*}{**SE**} & \multicolumn{2}{c}{**Z**} & \(p\)**-** & **Lower CI** & **Upper CI** \\  & & & **Score** & **Value** & **(95\%)** & **(95\%)** \\ \hline Subject & 0.000 & - & - & - & - & - \\ Success & 1.188 & 1.868 & 0.636 & 0.525 & \(-\)2.474 & 4.850 \\ Image & 0.000 & - & - & - & - & - \\ Success \(\times\) & \(-\)0.106 & 0.114 & \(-\)0.929 & 0.353 & \(-\)0.330 & 0.118 \\ ordinal number & \(-\)0.393 & 0.777 & 0.505 & 0.614 & \(-\)1.131 & 1.916 \\ Success \(\times\) image & 0.115 & 0.168 & 0.688 & 0.492 & \(-\)0.213 & 0.444 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Estimates of Parameters and their confidence intervals (CI). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Parameters**} & \multirow{2}{*}{**Coefficient**} & \multirow{2}{*}{**SE**} & \multicolumn{2}{c}{**Z**} & \(p\)**-** & **Lower CI** & **Upper CI** \\  & & & **Score** & **Value** & **(95\%)** & **(95\%)** \\ \hline Success \(\times\) & \multirow{2}{*}{\(-\)0.102} & \multirow{2}{*}{0.054} & \multirow{2}{*}{\(-\)1.876} & \multirow{2}{*}{0.061} & \multirow{2}{*}{\(-\)0.208} & \multirow{2}{*}{0.005} \\  & & & & & & \\ \(\times\) & & & & & & \\ \(\times\) & & & & & & \\ \(\times\) & & & & & & \\ \(\times\) & & & & & & \\ \(\times\) & & & & & & \\ \(\times\) & & & &case of colored and achromatic images, the odds ratio is 2.284/3.701 = 0.617. It means, that the odds of a subject to find the orientation of a colored figure is 0.617 times of the odds of finding the orientation of an achromatic image. In turn, the odds of succeeding in the achromatic test is 1/0.617 = 1.621 times of the chance of that in the colored test. Thus, the odds of success in achromatic images is higher than that in colored images. The coefficient of subject \(\times\) success \(\times\) image is 0.218. Because of the loglinear model, this value was multiplied by eight, and we took the exponential of this value with base \"e\" according to Formula (4) (odds ratio = e\({}^{8}\times\) 0.218 = 5.72). The analysis of the cross-tabulation of the subject \(\times\) success \(\times\) image parameter was prepared for the validation of that (see Table 7). In the case of the achromatic series of images, the odds of success of anomalous trichromats are 33/5 = 6.6 and 252/72 = 3.5 for normal trichromats. In regard to the proportion of these two odds, the odds ratio is 6.6/3.5 = 1.88. This shows that, in the case of the achromatic series, anomalous trichromats find the orientation of the Landolt-C figures easier than normal trichromats. In the case of the colored series of images, the odds of success of anomalous trichromats are 38/45 = 0.844 and 460/173 = 2.66 for normal trichromats. Therefore, the odds ratio is 0.844/2.66 = 0.317. This shows that, in the case of the colored series, anomalous trichromats find the orientation of the Landolt-C figures with more difficulty. Comparing the odds ratios (1.88/0.317 = 5.93), it can be concluded that, in the case of achromatic images, the chance that anomalous trichromats find the orientation of the Landolt-C figure is 5.93-times higher than that for normal trichromats. The estimation of the loglinear model is similar, as the value calculated of the model is 5.72, while the value of the chance ratio for success is 5.93 (5.93\(-\)5.72 = 0.21).