dscore: Calculate discrepancy score

In eventreport: Diagnose, Visualize, and Aggregate Event Report Level Data

Calculate discrepancy score

Description

This function computes the mean number of unique values minus one for each specified variable within each group specified by the group_var. It is designed to provide insights into the variability of each variable while adjusting for the minimum possible unique count.

Usage

dscore(data, group_var, variables)

Arguments

data	A dataframe containing the data to be analyzed.
group_var	A character string specifying the column name used for grouping the data.
variables	A character vector of column names in 'data' for which the mean number of unique values minus one is calculated.

Value

A tibble with each specified variable showing the mean of (unique values - 1) for each group. The data is grouped by the 'group_var' and returns the results in a wide format, where each variable is prefixed with "dscore_" to indicate the calculation.

Examples

df <- data.frame(
  group = c("A", "A", "B", "B", "B"),
  age = c(25, 25, 30, 35, 30),
  gender = c("Male", "Male", "Female", "Female", "Female"),
  income = c(50000, 50000, 60000, 65000, 60000)
)
result <- dscore(df, "group", c("age", "gender", "income"))
print(result)

eventreport documentation built on March 11, 2026, 1:07 a.m.