emcAdr (version 1.2)

p_value_cocktails: Used to add the p_value to each cocktail of cocktail list

Description

Used to add the p_value to each cocktail of cocktail list

Usage

p_value_cocktails(
  distribution_outputs,
  cocktails,
  ATCtree,
  observations,
  num_thread = 1L,
  filtred_distribution = FALSE
)

Value

A real valued number vector representing the p-value of the inputed cocktails computed on the distribution_outputs List.

Arguments

distribution_outputs

A list of distribution of cocktails of different sizes in order to compute the p_value for multiple cocktail sizes

cocktails

A list containing cocktails in the form of vector of integers (ATC index)

ATCtree

ATC tree with upper bound of the DFS (without the root)

observations

observation of the AE based on the medications of each patients (a DataFrame containing the medication on the first column and the ADR (boolean) on the second) on which we want to compute the risk distribution

num_thread

Number of thread to run in parallel if openMP is available, 1 by default

filtred_distribution

Does the p-values have to be computed using filtered distribution or normal distribution (filtered distribution by default)

Examples

# \donttest{
 data("ATC_Tree_UpperBound_2024")
 data("FAERS_myopathy")
 
  DistributionApproximationResults_size2 = DistributionApproximation(epochs = 10,
            ATCtree = ATC_Tree_UpperBound_2024, observations = FAERS_myopathy, Smax = 2)
            
  DistributionApproximationResults_size3 = DistributionApproximation(epochs = 10,
            ATCtree = ATC_Tree_UpperBound_2024, observations = FAERS_myopathy, Smax = 3)
            
  score_distribution_list = list(DistributionApproximationResults_size2,
                              DistributionApproximationResults_size3)

  cocktails = list(c(561, 904),
               c(1902, 4585))
 
  p_value_cocktails(score_distribution_list, cocktails, ATC_Tree_UpperBound_2024,
                    FAERS_myopathy)
# }