Hey, sorry I never got round to replying to this. Now the journal editor is asking about this! So I need to fix it.

The code of the model is below. In model1, they are all categorical binary variables, model2 has one continuous variable Intransitivity05, the others are categorical as in model1. I’ve also attached a subset of the data. Thank you

model1= brm (Case~ Affirmation+ Affectedness+ Causative+ Telicity+ Tense+ Punctuality+

Person+ NumberObj+ Mood+ Kinesis+ NumberSubj+

AgencySubj* AnimacyObj+ Participants* Causative+

Participants* AgencySubj+ AgencySubj* Causative+

Concreteness* Participants+ Count* Participants+

Group* Participants+ (1| Verb), data= training,

family=bernoulli (link=“logit” ),iter=3000 , cores=4 , seed=123 , save_all_pars = TRUE ,

control = list (max_treedepth = 15 ), prior=set_prior (“cauchy(0,2.5)” , class=“b” ),

set_prior (“cauchy(0,10)” , class=“Intercept” ))

model2_dat= brm (Case~ Transitivity05+ Causative+ Tense+

Person+ NumberSubj+ Group+ (1| Verb), data= training,

family=bernoulli (link=“logit” ),iter=3000 ,

cores=4 , seed=123 , save_all_pars = TRUE , control = list (max_treedepth = 15 ),

prior=set_prior (“cauchy(0,2.5)” , class=“b” ), set_prior (“cauchy(0,10)” , class=“Intercept” ))

mini_df.csv (635.9 KB)