> m2 <- clm(categorical_FOD_FODs ~ 0 + Condition_FODs:Language_used_FODs - 1, random = ~1|subject, data = indvar_FODs) > summary(m2) formula: categorical_FOD_FODs ~ 0 + Condition_FODs:Language_used_FODs - 1 data: indvar_FODs link threshold nobs logLik AIC niter max.grad cond.H logit flexible 3321 -2909.91 5861.83 6(0) 1.02e-12 2.3e+02 Coefficients: (1 not defined because of singularities) Estimate Std. Error z value Pr(>|z|) Condition_FODsA:Language_used_FODsEnglish 0.15985 0.16285 0.982 0.3263 Condition_FODsB:Language_used_FODsEnglish -0.35112 0.16186 -2.169 0.0301 * Condition_FODsC:Language_used_FODsEnglish -0.29190 0.16191 -1.803 0.0714 . Condition_FODsD:Language_used_FODsEnglish -0.13500 0.16302 -0.828 0.4076 Condition_FODsA:Language_used_FODsGerman -0.19718 0.32939 -0.599 0.5494 Condition_FODsB:Language_used_FODsGerman -0.47769 0.33140 -1.441 0.1495 Condition_FODsC:Language_used_FODsGerman -0.19718 0.32125 -0.614 0.5393 Condition_FODsD:Language_used_FODsGerman 0.09461 0.33130 0.286 0.7752 Condition_FODsA:Language_used_FODsHungarian 0.05442 0.33670 0.162 0.8716 Condition_FODsB:Language_used_FODsHungarian 0.16750 0.32145 0.521 0.6023 Condition_FODsC:Language_used_FODsHungarian -0.01134 0.32469 -0.035 0.9721 Condition_FODsD:Language_used_FODsHungarian -0.19718 0.32939 -0.599 0.5494 Condition_FODsA:Language_used_FODsItalian 0.24686 0.33351 0.740 0.4592 Condition_FODsB:Language_used_FODsItalian -0.51232 0.35069 -1.461 0.1440 Condition_FODsC:Language_used_FODsItalian -0.10817 0.31887 -0.339 0.7344 Condition_FODsD:Language_used_FODsItalian -0.19718 0.32939 -0.599 0.5494 Condition_FODsA:Language_used_FODsTurkish 0.06285 0.12448 0.505 0.6136 Condition_FODsB:Language_used_FODsTurkish -0.20397 0.12255 -1.664 0.0960 . Condition_FODsC:Language_used_FODsTurkish -0.20060 0.12271 -1.635 0.1021 Condition_FODsD:Language_used_FODsTurkish NA NA NA NA --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Threshold coefficients: Estimate Std. Error z value ascending|descending -0.08387 0.08884 -0.944 descending|identity 2.61638 0.10831 24.157 (199 observations deleted due to missingness) what does this test says? What should be the follow up analysis according to these results? please write analysis code accordingly.

m2 <- clm(categorical_FOD_FODs ~ 0 + Condition_FODs:Language_used_FODs - 1, random = ~1|subject, data = indvar_FODs)
summary(m2)