mb_proportions calculates lower/equivalent/higher difference proportions between two groups

mb_proportions(
  group_a,
  group_b,
  paired = FALSE,
  SESOI_lower = 0,
  SESOI_upper = 0,
  method = "algebraic",
  na.rm = FALSE,
  use_normal_distribution = FALSE
)

Arguments

group_a

Numeric vector. This group represents baseline/control, observed variable, Pre-test in the paired design, or "practical" measure

group_b

Numeric vector. This group represents experimental, predicted variable, Post-test in the paired design, or "criterion" measure

paired

Paired groups? Default is FALSE

SESOI_lower

Lower smallest effect size of interest threshold

SESOI_upper

Upper smallest effect size of interest threshold

method

Select "brute-force" or "algebraic" method to calculate proportions. Default is "algebraic"

na.rm

Should NAs be removed? Default is FALSE

use_normal_distribution

When estimating proportions algebraically, should normal or t-distribution be used. Default is FALSE (normal t-distribution)

Value

Data frame with lower, equivalent and higher columns

Examples

mb_proportions(rnorm(100), rnorm(100))
#> lower equivalent higher #> 1 0.5704212 0 0.4295788