evol_auc {sMSROC} | R Documentation |
Evolution of the AUCs
Description
Plots, in prognosis scenarios, the areas under the ROC curves computed by the sMSROC estimator for a sequence of times.
Usage
evol_auc(marker, status, observed.time, left, right,
time = 1, meth = c("L", "S", "E"), grid = 500)
Arguments
marker |
vector with the biomarker values. |
status |
numeric response vector. Only two values will be taken into account. The highest one is assumed to stand for the subjects having the event under study. The lowest value, for those who do not. Any other value will not be considered. It is mandatory in prognosis scenarios and right censorship. |
observed.time |
vector with the observed times for each subject, for prognosis scenarios under right censorship. Notice that these values may be the event times or the censoring times. |
left |
vector containing the lower edges of the observed intervals. It is mandatory in prognosis scenarios under interval censorship and ignored in other situations. |
right |
vector with the upper edges of the observed intervals. It is mandatory in prognosis scenarios under interval censorship and ignored in other situations. The infinity is admissible as value (indicated as inf). |
time |
vector of times at which the sMS ROC curve estimator will be computed. The default value is 1. |
meth |
method for approximating the predictive model
|
grid |
grid size for computing the AUC. Default value 500. |
Details
This function calls the sMSROC
function at each of the times indicated in the vector time
, and the AUC is computed according to the parameters indicated.
Value
A list with the following components:
evol.auc |
object of class |
time |
vector with the ordered values of the |
auc |
vector with the values of the AUCs computed at the times indicated at the |
See Also
sMSROC
Examples
# Example of the use of the evol.AUC function
data(ktfs)
DT = ktfs
aucs <- evol_auc(marker = DT$score,
status = DT$failure,
observed.time = DT$time,
time = seq(2:3),
meth = "E")
aucs$evol.auc