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>