AdaptiveBoxplot (version 0.1.1)

holm_boxplot: Family-Wise Error Rate (FWER) Boxplot

Description

Generates a boxplot where whisker lengths are determined by the Holm procedure to control the Family-Wise Error Rate (FWER), providing a conservative yet principled approach to outlier detection.

Usage

holm_boxplot(
  data,
  alpha = 0.05,
  kfwer = 1,
  group_col = NULL,
  value_col = NULL,
  ...
)

Value

A plot is drawn on the current graphics device.

Arguments

data

A numeric vector for a single boxplot, or a data frame for grouped boxplots.

alpha

The target FWER level. Defaults to 0.05.

kfwer

The "k" in k-FWER control. Defaults to 1 for standard FWER.

group_col

A string specifying the name of the grouping column in `data`.

value_col

A string specifying the name of the value column in `data`.

...

Additional arguments passed to the base boxplot function.

Details

This function is a graphical implementation of the p-value pipeline proposed by Gang, Lin, and Tong (2025). It uses robust estimators for the mean and standard deviation based on quartiles to calculate p-values for each observation, then applies the Holm procedure to determine a p-value threshold that controls the FWER. This method is generally more conservative than the FDR boxplot.

References

Gang, B., Lin, H., & Tong, T. (2025). Unifying Boxplots: A Multiple Testing Perspective.

See Also

bh_boxplot

Examples

# Single group example
set.seed(123)
data_single <- c(rnorm(50), 10, 12)
holm_boxplot(data_single, alpha = 0.05, main = "FWER Boxplot (Single Group)")

# Grouped data example
data_grouped <- data.frame(
  Category = rep(c("A", "B"), each = 100),
  Value = c(rnorm(100), rnorm(100, mean = 2, sd = 1.5))
)
holm_boxplot(data_grouped, group_col = "Category", value_col = "Value")