auc_ci_boot-internal {sMSROC}

Confidence intervals for the AUC (bootstrap)

Description

Computation of confidence intervals for the AUC based on Bootstrap Percentile.

Usage

auc_ci_boot(marker, outcome, status, observed.time, left, right, time,
                    data_type, meth, grid, probs, ci.cl, ci.nboots, parallel,
                    ncpus, all)

Arguments

marker

vector with the biomarker values.

outcome

vector with the condition of the subjects as positive, negative or unknown at the considered time time.

status

response vector.

observed.time

vector with the observed times for each subject.

left

vector with the lower edges of the observed intervals.

right

vector with the upper edges of the observed intervals.

time

point of time at which the sMS ROC curve estimator will be computed.

data_type

scenario handled.

meth

method for approximating the predictive model P(D|X=x).

grid

grid size.

probs

vector containing the probabilities estimated through the predictive model.

ci.cl

confidence level at which the confidence intervals will be computed.

ci.nboots

number of bootstrap samples.

parallel

indicates whether parallel computing will be performed or not.

ncpus

number of CPUs to use if parallel computing is performed.

all

indicates whether the probabilities from the predictive model will be considered for all individuals, or only for those whose outcome value (condition) is unknown.

Value

List with two components:

ic.l

lower edge of the confidence interval.

ic.u

upper edge of the confidence interval.