Original post is here. I have changed the order of \(\beta_n\) coefficients.

Original post is here.

Continuing with the new regression model. Now it's the discrete dataset.

It works for the original dataset pretty well. Here's what comes out:

I have just discovered a better model for participants scores in the experiment. This used to be our prime model:
```prettyprint
model <- lmer(score ~ nstates_amp_and_freq_n + (1 | id) + (1 |condition:phase) , data=all, REML=F)
```
I have discovered the following one outperforms this for both the original and the discrete datasets, and is much easier to interpret:
```prettyprint
model <- lmer(score ~ nstates_amp_and_freq_n:phase_order:phase + (1|id), data=all, REML=F)
```
Of course, we are using MCMC samples, so the model declaration becomes: