View source: R/biomarker_utils.R
Perform.UnivROC | R Documentation |
Perform Classical Univariate ROC
Perform.UnivROC(mSetObj=NA, feat.nm, version,
format="png", dpi=72, isAUC, isOpt, optMethod, isPartial, measure, cutoff)
mSetObj |
Input the name of the created mSetObj (see InitDataObjects) |
feat.nm |
Input the name of the feature to perform univariate ROC analysis |
version |
image version mark, can be any character |
format |
Select the image format, png, of pdf. |
dpi |
Input the dpi. If the image format is pdf, users need not define the dpi. For png images, the default dpi is 72. It is suggested that for high-resolution images, select a dpi of 300. |
isAUC |
Logical, select T to compute the 95 percent confidence interval band and "F" to not |
isOpt |
Logical, show the optimal cutoff, T to show it and F to not |
optMethod |
Select the optimal cutoff by using either closest.topleft for closest to top-left corner or youden for farthest to the diagonal line (Youden) |
isPartial |
Logical, input T to calculate a partial ROC curve, and F to not |
measure |
Select the parameter to limit the calculation of the partial ROC curve, se for the X-axis (maximum false-positive rate) and sp for the Y-axis, representing the minimum true positive-rate |
cutoff |
Input the threshold to limit the calculation of the partial ROC curve, the number must be between 0 and 1. |
Jeff Xia jeff.xia@mcgill.ca McGill University, Canada License: GNU GPL (>= 2)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.