> 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 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)
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