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Tailor Disproportionality Threshold

Source: R/disproportionality_analysis.R
tailor_disproportionality_threshold.Rd

This function analyzes a data frame of disproportionality metrics and categorizes signals based on specified thresholds.

Usage

tailor_disproportionality_threshold(
  disproportionality_df,
  minimum_cases = 3,
  log2_threshold = 0,
  frequentist_threshold = 1,
  multiple_comparison = TRUE
)

Arguments

disproportionality_df

A data frame containing disproportionality metrics. Generated by disproportionality_analysis.

minimum_cases

An integer specifying the minimum number of cases required to consider the signal. Defaults to 3.

log2_threshold

A numeric value specifying the threshold for the Information Component (IC) signal. Defaults to 0.

frequentist_threshold

A numeric value specifying the threshold for the Reporting Odds Ratio (ROR) signal. Defaults to 1.

multiple_comparison

A logical value indicating whether to apply multiple comparison adjustments (e.g., Bonferroni correction). Defaults to TRUE.

Value

A data frame with two new columns: ROR_signal and IC_signal, categorizing the signals based on the provided thresholds.

Details

The function categorizes signals into four levels:

  • "not enough cases": when the number of cases is less than minimum_cases.

  • "no SDR": when the signal does not meet the specified threshold.

  • "weak SDR": when the signal disappear under multiple comparison adjustments.

  • "SDR": when the signal remain after multiple comparison.

Examples

disproportionality_df <- disproportionality_analysis(
  drug_selected = "paracetamol",
  reac_selected = "headache",
  temp_drug = sample_Drug,
  temp_reac = sample_Reac
)

disproportionality_df <- tailor_disproportionality_threshold(disproportionality_df,
  minimum_cases = 5
)