> 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 with interaction effect 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.

# for categorical_FOD_FODs

MultinomialLogisticRegression_FODs <- multinom(categorical_FOD_FODs ~ Condition_FODs + Language_used_FODs + Condition_FODs:Language_used_FODs, data = indvar_FODs)
summary(MultinomialLogisticRegression_FODs)

# Call:
# multinom(formula = categorical_FOD_FODs ~ Condition_FODs + 
#     Language_used_FODs + Condition_FODs:Language_used_FODs, 
#     data = indvar_FODs)
# 
# Coefficients:
#                             (Intercept)  Condition_FODsB  Condition_FODsC 
#                                       1         -0.87860          0.41173 
#                             Condition_FODsD  Language_used_FODsGerman 
#                                       1.0              -0.12083 
#