Just for good measures, I am running BRMS 2.14.4 on Win10

I am trying to model and visualize an ordinal factor predicted by an interaction of another factor and a continuous feature.

I have tweaked the trolley data from Mcelreath’s rethinking package to approximate the kind of data I have. There is probably not an actual pattern in this data which is why I am not caring about convergence and such.

Ideally. I am interested in the rate of each response for education over the duration of the experiment as can be seen here on raw data.

My model is specified:

```
brm(response ~ edu*mo(order) + (1|id), data= data,
family = cumulative(threshold = "flexible"),
chains = 2)
```

I have tried to see if there is some straightforward way to make the plot which corresponds to the above using

```
conditional_effects(m1, categorical=T)
```

And

```
conditions <- make_conditions(m1, "response")
conditional_effects(m1,categorical=TRUE, conditions = conditions)
```

Neither plot gives me exactly what I am hoping for. I hope that there is some easy way to achieve it? The code to replicate the above is here conditional effect - Pastebin.com

Thanks for reading.