model <- multinom(categorical_FOD_FODs ~ Condition_FODs + Language_used_FODs + Condition_FODs*Language_used_FODs, indvar_FODs) summary(model) write code for the post-hoc analysis

## https://stats.idre.ucla.edu/r/dae/multinomial-logistic-regression/

# Example of a multinomial logistic regression
#
#  The data are from the example in Agresti (2013), Categorical Data Analysis, 3rd ed.,
#  Table 10.2, p. 497.
#
#  The data are from a survey to determine the preferred vacation site
#  of 100 people, who were asked to pick their first, second, and third
#  choice among the following four sites.  The data are coded as
#  0 = no preference, 1 = first choice, 2 = second choice, 3 = third choice.
#
#  The response is categorical, with four categories:
#  1 = Grand Canyon, 2 = Redwood Forest, 3 = Yosemite, 4 = Yellowstone.
#  There are four predictors: age, sex, education, and income.
#  The predictors are continuous.
#
#  The model is
#     logit(p[i,j]) = beta[0,j] +