# Summarize Posterior Distributions of Model Differences

Source:`R/contrasts.R`

`summary.posterior_diff.Rd`

Credible intervals are created for the differences. Also, region of practical equivalence (ROPE) statistics are computed when the effective size of a difference is given.

## Usage

```
# S3 method for posterior_diff
summary(object, prob = 0.9, size = 0, ...)
```

## Arguments

- object
An object produced by

`contrast_models()`

.- prob
A number p (0 < p < 1) indicating the desired probability mass to include in the intervals.

- size
The size of an effective difference in the units of the chosen metric. For example, a 5 percent increase in accuracy (

`size = 0.05`

) between two models might be considered a "real" difference.- ...
Not currently used

## Details

The ROPE estimates included in the results are the
columns `pract_neg`

, `pract_equiv`

, and `pract_pos`

. `pract_neg`

integrates the portion of the posterior below `-size`

(and
`pract_pos`

is the upper integral starting at `size`

). The
interpretation depends on whether the metric being analyzed is
better when larger or smaller. `pract_equiv`

integrates between
`[-size, size]`

. If this is close to one, the two models are
unlikely to be practically different relative to `size`

.

## Examples

```
data("ex_objects")
summary(contrast_samples)
#> # A tibble: 2 × 9
#> contrast probability mean lower upper size pract_neg pract_equiv
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 logisti… 1 3.29e-2 0.0196 0.0462 0 NA NA
#> 2 logisti… 0.472 -5.40e-4 -0.0142 0.0130 0 NA NA
#> # ℹ 1 more variable: pract_pos <dbl>
summary(contrast_samples, size = 0.025)
#> # A tibble: 2 × 9
#> contrast probability mean lower upper size pract_neg pract_equiv
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 logisti… 1 3.29e-2 0.0196 0.0462 0.025 0 0.168
#> 2 logisti… 0.472 -5.40e-4 -0.0142 0.0130 0.025 0.0036 0.994
#> # ℹ 1 more variable: pract_pos <dbl>
```