`tidy`

can be used on an object produced by `perf_mod()`

to create a data frame with a column for the model name and
the posterior predictive distribution values.

## Usage

```
# S3 method for perf_mod
tidy(x, seed = sample.int(10000, 1), ...)
```

## Arguments

- x
An object from

`perf_mod()`

- seed
A single integer for sampling from the posterior.

- ...
Not currently used

## Details

Note that this posterior only reflects the variability
of the groups (i.e. the fixed effects). This helps answer the
question of which model is best *for this data set*. If does not
answer the question of which model would be best on a new
resample of the data (which would have greater variability).