> table(indvar_FODs$categorical_FOD_FODs) ascending descending identity 1683 1432 206 > table(indvar_FODs$Condition_FODs) A B C D 880 880 880 880 > table(indvar_FODs$Language_used_FODs) English German Hungarian Italian Turkish 880 160 160 160 2160 categorical_FOD_FODs is the dependent variable. please apply multinomial logistic regression. treat each level of the Condition_FODs variable (4 levels) and Language_used_FODs variable (5 levels) equally. include the interaction effect of variables in the analysis. Question 2: m1 <- glm(categorical_FOD_FODs ~ Condition_FODs*Language_used_FODs, data = indvar_FODs, family = "multinomial") Error in get(family, mode = "function", envir = parent.frame()) : object 'multinomial' of mode 'function' was not found

library(nnet)
m1 <- multinom(categorical_FOD_FODs ~ Condition_FODs*Language_used_FODs, data = indvar_FODs)
summary(m1)
Call:
multinom(formula = categorical_FOD_FODs ~ Condition_FODs * Language_used_FODs, 
    data = indvar_FODs)

Coefficients:
                                             (Intercept) Condition_FODsA Condition_FODsB 
                                               -5.56764                0.16689        -0.01620 
Condition_FODsC Condition_FODsD Language_used_FODsEnglish 
                                                0.09732         -0.16689          0.36466 
Language_used_FODsGerman Language_used_FODsHungarian Language_used_FODsItalian 
                                          -0.36466                -0.36466         -0.03095 
Language_used_F