generate_data_roc: Generate binary data (ROC model)

In maxwestphal/DTAmc: Diagnostic Test Accuracy studies with multiple comparisons

Description

Generate binary data (ROC model)

Usage

generate_data_roc(
  n = 100,
  prev = c(0.5, 0.5),
  random = FALSE,
  m = 10,
  auc = seq(0.85, 0.95, length.out = 5),
  rho = c(0.25, 0.25),
  e = 10,
  k = 100,
  delta = 0,
  modnames = paste0("model", 1:m),
  corrplot = FALSE,
  ...
)

Arguments

n	integer, total sample size
prev	numeric, disease and healthy prevalence (adds up to 1)
random	logical, random sampling (TRUE) or fixed prevalence (FALSE)
m	integer, number of models
auc	numeric, vector of AUCs of biomarkers
rho	numeric, vector (length 2) of correlations between biomarkers
e	numeric, emulates better (worse) model selection quality with higher (lower) values of e
k	integer, technical parameter which adjusts grid size, can stay at default (1000)
delta	numeric, specify importance of sensitivity and specificity (default 0)
modnames	character, model names (length m)
corrplot	logical (default: FALSE), if TRUE do not return data but instead plot correlation matrices for final binary data
...	further arguments (currently unused)

Value

Generated binary dataset

Examples

data <- generate_data_roc()
head(data)

maxwestphal/DTAmc documentation built on Dec. 21, 2021, 3:52 p.m.