se_auc: Compute standard error of AUC score, using its equivalence to...

In jpgard/auctestr: Statistical Testing for AUC Data

Description

Compute standard error of AUC score, using its equivalence to the Wilcoxon statistic.

Usage

se_auc(auc, n_p, n_n)

Arguments

auc	value of A' statistic (or AUC, or Area Under the Receiver operating characteristic curve) (numeric).
n_p	number of positive cases (integer).
n_n	number of negative cases (integer).

References

Hanley and McNeil, The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology (1982) 43 (1) pp. 29-36.

Fogarty, Baker and Hudson, Case Studies in the use of ROC Curve Analysis for Sensor-Based Estimates in Human Computer Interaction, Proceedings of Graphics Interface (2005) pp. 129-136.

See Also

Other fbh method: auc_compare, fbh_test

Examples

se_auc(0.75, 20, 200)
## standard error decreases when data become more balanced over
## positive/negative outcome class, holding sample size fixed
se_auc(0.75, 110, 110)
## standard error increases when sample size shrinks
se_auc(0.75, 20, 20)

jpgard/auctestr documentation built on May 29, 2019, 1:08 a.m.