draw_data_lfc: Generate binary data (LFC model)

In cases: Stratified Evaluation of Subgroup Classification Accuracy

Generate binary data (LFC model)

Description

Generate binary data (LFC model)

Usage

draw_data_lfc(
  n = 100,
  prev = c(0.5, 0.5),
  random = FALSE,
  m = 10,
  se = 0.8,
  sp = 0.8,
  B = round(m/2),
  L = 1,
  Rse = diag(rep(1, m)),
  Rsp = diag(rep(1, m)),
  modnames = paste0("model", 1:m),
  ...
)

Arguments

n	(numeric) integer, total sample size
prev	(numeric) disease and healthy prevalence (length 2, adds up to 1)
random	(logical) random sampling (TRUE) or fixed prevalence (FALSE)
m	(numeric) integer, number of models
se	(numeric) sensitivity (length 1)
sp	(numeric) specificity (length 1)
B	(numeric) integer, between 1 and m, specifies how many sensitivity values are projected to 1
L	(numeric) worst alternative is computed under side condition Acc <= L (default value L=1 corresponds to true LFC where values are projected to 1)
Rse	(matrix) correlation matrix for empirical sensitivities (m x m)
Rsp	(maxtrix) correlation matrix for empirical specificities (m x m)
modnames	(modnames) character, model names (length m)
...	(any) further arguments (currently unused)

Value

(list)
list of matrices including generated binary datasets (1: correct prediction, 0: incorrect prediction) for each subgroup (specificity, sensitivity)

Examples

data <- draw_data_lfc()
head(data)

cases documentation built on April 3, 2025, 9:24 p.m.