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.

# 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

Value

A data frame with interval and ROPE statistics for each comparison.

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