ROCplot: ROCplot

In bimixt: Estimates Mixture Models for Case-Control Data

Description

Creates a ROC plot.

Usage

ROCplot(model, direction = "auto")

Arguments

model

an object of type model from bimixt.model

direction

same as roc: same as pROC: 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

Plots empirical and model-based estimates of the receiver operator characteristic (ROC) curve. The empirical plot comes from 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 ROCcoords ROCauc ROCpauc

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")
ROCplot(model)

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