BayesianReasoning (version 0.4.0)

process_variables: process_variables Checks and process main variables, checks for errors, creates defaults

Description

process_variables Checks and process main variables, checks for errors, creates defaults

Usage

process_variables(
  min_Prevalence = NULL,
  max_Prevalence = NULL,
  Sensitivity = NULL,
  Specificity = NULL,
  limits_Sensitivity = NULL,
  limits_Specificity = NULL,
  overlay_labels = NULL,
  overlay_position_FP = NULL,
  overlay_position_FN = NULL,
  overlay_prevalence_1 = NULL,
  overlay_prevalence_2 = NULL,
  PPV_NPV = "PPV",
  one_out_of = NULL,
  overlay = "",
  steps_matrix = 100
)

Arguments

min_Prevalence

x in the "x out of y" prevalence (y-axis): [1-Inf]

max_Prevalence

y in the "x out of y" prevalence (y-axis): [1-Inf]

Sensitivity

Sensitivity of the test: [0-100]

Specificity

Specificity of the test: [0-100]

limits_Sensitivity

c(min Sensitivity, max Sensitivity)

limits_Specificity

c(min Specificity, max Specificity)

overlay_labels

vector with labels for each overlay point

overlay_position_FP

FP value (position in the x-axis) for each point in the overlay. For example: c(7, 8, 9, 12, 14, 14)

overlay_position_FN

FN value (position in the x-axis) for each point in the overlay. For example: c(7, 8, 9, 12, 14, 14)

overlay_prevalence_1

Prevalence value (position in the y-axis) for each point in the overlay. For example: c(1, 1, 1, 2, 1, 1)

overlay_prevalence_2

Prevalence value (position in the y-axis) for each point in the overlay. For example: c(26, 29, 44, 69, 227, 1667)

PPV_NPV

Should show PPV or NPV ["PPV", "NPV"]

one_out_of

Show y scale as 1 out of x [TRUE, FALSE] FALSE by default

overlay

Type of overlay: ["line", "area"]

steps_matrix

with of PPV/NPV matrix. 100 by default