Last data update: 2014.03.03

 R: ROCpauc
ROCpaucR Documentation

ROCpauc

Description

Finds the partial area under the ROC curve.

Usage

ROCpauc(model, spec.lower = 0.95, spec.upper = 1, direction = "auto")

Arguments

model

an object of type model from bimixt.model

spec.lower

a value between 0 and 1 that serves as the lower bound of the specificity to be used in the PAUC calculation

spec.upper

a value between 0 and 1 that serves as the upper bound of the specificity to be used in the PAUC calculation

direction

same as roc: the direction in which to make the comparison. "auto" (default): automatically define in which group the median is higher and take the direction accordingly. ">": if the predictor values for the control group are higher than the values of the case group (controls > t >= cases). "<": if the predictor values for the control group are lower or equal than the values of the case group (controls < t <= cases).

Value

Returns the partial area under the curve (pAUC) for the fitted and empirical receiver operator characteristic (ROC) curves between spec.lower and spec.upper. The empirical pAUC value is calculated using the pROC package.

Author(s)

Michelle Winerip, Garrick Wallstrom, Joshua LaBaer

References

Xavier Robin, Natacha Turck, Alexandre Hainard, et al. (2011) "pROC: an open-source package for R and S+ to analyze and compare ROC curves". BMC Bioinformatics, 7, 77. DOI: 10.1186/1471-2105-12-77.

See Also

auc ROCauc ROCcoords ROCplot

Examples

cases=rmix(50,10,1.2,20,1.3,.7)
controls=rmix(50,9,1.1,17,1.3,.95)
model= bimixt.model(cases,controls,"4c") 
ROCpauc(model, spec.lower = .85, spec.upper = 1)

Results


Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and IMSBIO