ROCauc: ROCauc

In bimixt: Estimates Mixture Models for Case-Control Data

Description

Finds the area under the ROC curve.

Usage

ROCauc(model, direction = "auto")

Arguments

model	an object of type model from bimixt.model
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 values for the control group are higher than the values of the case group (controls > t >= cases). "<": if the values for the control group are lower than the values of the case group (controls < t <= cases).

Value

Returns the area under the curve (AUC) for the fitted and empirical receiver operator characteristic (ROC) curves. The empirical AUC value is calculated using the pROC package.

Author(s)

Michelle Winerip, Garrick Wallstrom, Joshua LaBaer

References

Xavier Robin, Natacha Turck, Alexandre Hainard, Natalia Tiberti, Fr?d?rique Lisacek, Jean-Charles Sanchez and Markus M?ller (2011). "pROC: an open-source package for R and S+ to analyze and compare ROC curves". BMC Bioinformatics, 12, p. 77. DOI: 10.1186/1471-2105-12-77

See Also

auc ROCpauc 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")
ROCauc(model)

bimixt documentation built on May 2, 2019, 3:31 p.m.