find_optimal_coef: Find Adaptive Boxplot Coefficient 'coef' via Grid Search

In MDDC: Modified Detecting Deviating Cells Algorithm in Pharmacovigilance

Find Adaptive Boxplot Coefficient 'coef' via Grid Search

Description

This function performs a grid search to determine the optimal adaptive boxplot coefficient 'coef' for each column of a contingency table, ensuring the target false discovery rate (FDR) is met.

Usage

find_optimal_coef(
  contin_table,
  n_sim = 1000,
  target_fdr = 0.05,
  grid = 0.1,
  col_specific_cutoff = TRUE,
  exclude_small_count = TRUE
)

Arguments

contin_table	A matrix representing the I \times J contingency table.
n_sim	An integer specifying the number of simulated tables under the assumption of independence between rows and columns. Default is 1000.
target_fdr	A numeric value specifying the desired level of false discovery rate (FDR). Default is 0.05.
grid	A numeric value representing the size of the grid added to the default value of coef = 1.5 as suggested by Tukey. Default is 0.1.
col_specific_cutoff	Logical. If TRUE, then a single value of the coefficient is returned for the entire dataset, else when FALSE specific values corresponding to each of the columns are returned.
exclude_small_count	A logical indicating whether to exclude cells with counts smaller than or equal to five when computing boxplot statistics. Default is TRUE.

Value

A list with the following components:

coef: A numeric vector containing the optimal coefficient 'coef' for each column of the input contingency table.

FDR: A numeric vector with the corresponding false discovery rate (FDR) for each column.

Examples

# This example uses the statin49 data
data(statin49)
find_optimal_coef(statin49)

MDDC documentation built on April 11, 2025, 5:45 p.m.