Hi everyone. I just learned how to do the Bayesian ordinal logistic regression model after reading Bürkner & Vuorre’s (2019) tutorial. I followed their steps, tried different models, compared them, and found that the following model with the interactional terms has the best fit:
Scale is the Likert scale from 1 to 9
Condition is the categorical variable with four levels: Condition_a (used as the reference level), Condition_b, Condition_c, Condition_d
Language is the categorical variable with two levels: Language_English (used as the reference level) and Language_Spanish
Honestly, I don’t know how to further analyze the interactional term in Bayesian modelling. I mean, if I would like to treat Condition as the moderator, and see at each level of Condition whether Language has an effect, what should I do here?
I saw a similar post on this forum where someone suggested using hypothesis() function. Honestly, after reading that post and the usage of hypothesis(), I am not quite sure that I fully understand it.
For instance, if I use
hypothesis(model, (“Condition_b + Condition_b*Language_Spanish = 0”))
The result looks like this:
Hypothesis Tests for class b:
Estimate Est.Error CI.Lower CI.Upper Evid.Ratio Post.Prob Star
3.88 0.21 3.48 4.3 NA NA *
What is being tested here? How do I interpret these numbers?