draw_data_roc {cases} | R Documentation |
Generate binary data (ROC model)
Description
Generate binary data (ROC model)
Usage
draw_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),
dist = c("normal", "exponential"),
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 |
dist |
character, either "normal" or "exponential" specifying the subgroup biomarker distributions |
e |
numeric, emulates better (worse) model selection quality with higher (lower) values of e |
k |
integer, technical parameter which adjusts grid size |
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 <- draw_data_roc()
head(data)