roc.area.test {clinfun} | R Documentation |
Nonparametric area under the ROC curve
Description
Computes the nonparametric area under the ROC curve and its variance based on U-statistic theory (DDCP).
Usage
roc.area.test(markers, status)
## S3 method for class 'roc.area.test'
print(x, ...)
Arguments
markers |
The marker values for each subject. If there are more than one markers then this should be a matrix. |
status |
binary disease status indicator |
x |
object of class roc.area.test output from this function. |
... |
optional arguments to the print function. |
Details
It calculates the area and its variance. For more than one marker it calculates the statistic to test for the equality of all AUCs. This statistic has a standard normal reference distribution for two variables and chi-square with number of variables minus 1.
Value
a list with the following elements
area |
estimated area. |
var |
estimated variance (matrix). |
stat |
test statistic for equality of AUCs. Is not returned when only one diagnostic marker is present. |
p.value |
the p-value for the test of equality (2-sided). |
df |
the degrees of freedom of the chi-square. |
The "print" method formats and returns the output.
References
DeLong, E. R., D. M. DeLong, and D. L. Clarke-Pearson. 1988. Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach. Biometrics 44:837-845.
Examples
g <- rep(0:1, 50)
x <- rnorm(100) + g
y <- rnorm(100) + g
z <- rnorm(100) + g
roc.area.test(cbind(x,y), g)
roc.area.test(cbind(x,y,z), g)
y1 <- y + 0.75*g
roc.area.test(cbind(x,y1), g)