Ordinal regession interpretation

I have two-way interaction model. I would like to specify an
adjacent-category model, and I use family = acat(). I use the cs function with the interaction term:

fit_model <- brm(rating  ~ 1 + cs(var1 * var2) + (1|participant) +
                   (1|id_script),family = acat(link = "logit"), prior = prior_ma, data = DF,
                 warmup = 2000, iter = 4000,  seed=123)

However, in the summary(fit) I get only intercept for one part beside the major effect of var1 and var 2 and the random effects . For example:

Var1Leve1Var2Level1[1] -0.54 0.14 -0.77 -0.29 1.03 116 51
Var1Leve1Var2Level1[2] -0.23 0.21 -0.69 0.15 1.05 60 34
Var1Leve1Var2Level1[3] -0.08 0.25 -0.53 0.39 1.08 50 63
Var1Leve1Var2Level1[4] 0.08 0.30 -0.45 0.71 1.06 52 51
Var1Leve1Var2Level1[5] -0.28 0.24 -0.75 0.17 1.03 61 61
Var1Leve1Var2Level1[6] -0.47 0.26 -0.94 0.03 1.01 61 58
Var1Leve1Var2Level1[7] -0.20 0.33 -0.96 0.37 1.06 45 30
Var1Leve1Var2Level1[8] -0.33 0.29 -0.89 0.17 1.04 64 43

What I’m doing wrong?

Please also provide the following information in addition to your question:

  • Operating System: Windows 10 Home
  • brms Version: 2.19

Don’t forget to add relevant tags to your topic (top right of this form) especially for application area. Delete this text before posting your question :-) Thx!