gROC_param {movieROC} | R Documentation |
Build a binormal ROC curve for a univariate marker
Description
This function builds a univariate ROC curve (standard or general) assuming the binormal scenario with parameters being the sample estimates. It returns a ‘groc’ object, a list of class ‘groc’.
Usage
gROC_param(X, D, side = c("right", "left", "both", "both2"), N = NULL, ...)
Arguments
X |
Vector of marker values. |
D |
Vector of response values. Two levels; if more, the two first ones are used. |
side |
Type of ROC curve. One of |
N |
Number indicating the length of the vector of FPR considered to build the ROC curve:
|
... |
Other parameters to be passed. Not used. |
Details
This function's main job is to estimate an ROC curve for a univariate marker
under one of these considerations: larger values of the marker are associated
with a higher probability of being positive (resulting in the right-sided
ROC curve, ), the opposite (left-sided ROC curve,
), when both smaller and larger values of the marker are
associated with having more probability of being positive (gROC curve,
), the opposite (opposite gROC curve,
).
Value
A list of class ‘groc’ with the following fields:
controls , cases |
Marker values of negative and positive subjects, respectively. |
levels |
Levels of response values. |
side |
Type of ROC curve. |
t |
Vector of false-positive rates. |
roc |
Vector of values of the ROC curve for |
c |
Vector of marker thresholds resulting in ( |
xl , xu |
Vectors of marker thresholds resulting in ( |
auc |
Area under the curve estimate. |
a , b |
Estimates for parameters |
p0 |
Estimate of the "central value", |
References
P. Martínez-Camblor and J. C. Pardo-Fernández (2019) “Parametric estimates for the receiver operating characteristic curve generalization for non-monotone relationships”. Statistical Methods in Medical Research, 28(7): 2032–2048. DOI: doi:10.1177/0962280217747009.
Examples
data(HCC)
# ROC curve estimates for gene 03515901 and response tumor assuming the binormal scenario
gROC_param(X = HCC[,"cg03515901"], D = HCC$tumor) # Standard right-sided ROC curve
gROC_param(X = HCC[,"cg03515901"], D = HCC$tumor, side = "left") # Left-sided ROC curve
gROC_param(X = HCC[,"cg03515901"], D = HCC$tumor, side = "both") # gROC curve