auctestr (version 1.0.0)

fbh_test: Apply z-test for difference between auc_1 and auc_2 using FBH method.

Description

Apply z-test for difference between auc_1 and auc_2 using FBH method.

Usage

fbh_test(auc_1, auc_2, n_p, n_n)

Arguments

auc_1

value of A' statistic (or AUC, or Area Under the Receiver operating characteristic curve) for the first group (numeric).

auc_2

value of A' statistic (or AUC, or Area Under the Receiver operating characteristic curve) for the second group (numeric).

n_p

number of positive observations (needed for calculation of standard error of Wilcoxon statistic) (numeric).

n_n

number of negative observations (needed for calculation of standard error of Wilcoxon statistic) (numeric).

Value

numeric, single aggregated z-score of comparison A'_1 - A'_2.

References

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, se_auc

Examples

# NOT RUN {
## Two models with identical AUC return z-score of zero
fbh_test(0.56, 0.56, 1000, 2500)
## Compare two models; note that changing order changes sign of z-statistic
fbh_test(0.56, 0.59, 1000, 2500)
fbh_test(0.59, 0.56, 1000, 2500)
# }

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