Impact: Impact effect size measure

In ImpactEffectsize: Calculation and Visualization of the Impact Effect Size Measure

Impact effect size measure

Description

Calculates the Impact effect size measure that is based on the group distance and the difference in the shape of the data distribution between two groups.

Usage

Impact(Data, Cls, PlotIt = FALSE, pde = TRUE, 
  col = c("red","blue"), meanLines = FALSE, medianLines = FALSE, ...)

Arguments

Data	Numeric vector containing the values of both groups.
Cls	Grouping vector or factor of same length as Data, containing exactly two distinct classes.
PlotIt	Logical; if TRUE, plots the probability density function (PDF) of the two groups using Pareto density estimation or kernel density as fallback.
pde	Logical; if TRUE, attempts Pareto Density Estimation (PDE) for the PDFs in the plot. Ignored if PlotIt = FALSE.
col	Character vector of length two specifying colors for the two groups in the plot. Ignored if PlotIt = FALSE.
meanLines	Logical; if TRUE, draws vertical lines at group means in the plot. Ignored if PlotIt = FALSE.
medianLines	Logical; if TRUE, draws vertical lines at group medians in the plot. Ignored if PlotIt = FALSE.
...	Further graphical parameters passed to the plotting function if PlotIt = TRUE.

Details

The Impact effect size measure combines central tendency differences (based on group medians) and morphological differences (based on Pareto density estimation). If Pareto density estimation fails or is disabled, the density plots fallback to standard kernel density estimates. The function can optionally plot these densities along with mean and/or median reference lines.

Value

Returns a list with the following components:

Impact

Numeric scalar; the combined effect size measure based on difference in medians and distribution shapes.

MorphDiff

Numeric scalar; the extent of difference in shapes of the probability density functions.

CTDiff

Numeric scalar; the extent of difference in group medians.

density_df

Data frame with columns PDEKernels, pde_Cls1, pde_Cls2 containing the density kernel points and Pareto densities for each group. This may be empty if Pareto density estimation was not successful or disabled.

Author(s)

Jorn Lotsch and Alfred Ultsch

References

Lotsch, J., and Ultsch, A. (2019): ImpactEffectsize – an R Package for calculation and visualisation of the Impact distance and shape based effect size measure.

Examples

## Example 1: Use Impact with plotting
data("FeatureselectionData")
ImpactSize <- Impact(Data = FeatureselectionData$Var0011, 
  Cls = FeatureselectionData$Classes, PlotIt = TRUE)
  
## Example 2: Impact without plotting
ImpactSize <- Impact(Data = FeatureselectionData$Var0011, 
  Cls = FeatureselectionData$Classes, PlotIt = FALSE)

## example 2
data("BcellLymphomaCD79")
data("FeatureselectionData")
data("FlowcytometricData")
data("SameMeansData")
data("StocksFluctuation")

ImpactEffectsize documentation built on Sept. 9, 2025, 5:49 p.m.