PEM: Percentage exceeding the median

In SingleCaseES: A Calculator for Single-Case Effect Sizes

Description

Calculates the percentage exceeding the median (PEM) index (Ma, 2006).

Usage

PEM(
  A_data,
  B_data,
  condition,
  outcome,
  baseline_phase = unique(condition)[1],
  improvement = "increase"
)

Arguments

A_data	vector of numeric data for A phase. Missing values are dropped.
B_data	vector of numeric data for B phase. Missing values are dropped.
condition	vector identifying the treatment condition for each observation in the series.
outcome	vector of outcome data for the entire series.
baseline_phase	character string specifying which value of condition corresponds to the baseline phase. Defaults to first observed value of condition.
improvement	character string indicating direction of improvement. Default is "increase".

Details

For an outcome where increase is desirable, PEM is calculated as the proportion of observations in the B phase that exceed the median observation from the A phase. For an outcome where decrease is desirable, PEM is calculated as the proportion of observations in the B phase that are less than the median observation from the A phase. Ties are counted with a weight of 0.5. The range of PEM is [0,1].

Value

Numeric value

References

Ma, H.-H. (2006). An alternative method for quantitative synthesis of single-subject researches: Percentage of data points exceeding the median. Behavior Modification, 30(5), 598–617. doi:doi: 10.1177/0145445504272974

Examples

A <- c(20, 20, 26, 25, 22, 23)
B <- c(28, 25, 24, 27, 30, 30, 29)
PEM(A_data = A, B_data = B)

SingleCaseES documentation built on Sept. 30, 2021, 5:09 p.m.