AUC: AUC for cv.ncvsurv objects

In pbreheny/ncvreg: Regularization Paths for SCAD and MCP Penalized Regression Models

AUC for cv.ncvsurv objects

Description

Calculates the cross-validated AUC (concordance) from a cv.ncvsurv object.

Usage

## S3 method for class 'cv.ncvsurv'
AUC(obj, ...)

Arguments

obj	A cv.ncvsurv object. You must run cv.ncvsurv() with the option returnY=TRUE in order for AUC() to work.
...	For S3 method compatibility; not used

Details

The area under the curve (AUC), or equivalently, the concordance statistic (C), is calculated according to the procedure described in van Houwelingen and Putter (2011). The function calls survival::concordancefit(), except cross-validated linear predictors are used to guard against overfitting. Thus, the values returned by AUC.cv.ncvsurv() will be lower than those you would obtain with concordancefit() if you fit the full (unpenalized) model.

Author(s)

Patrick Breheny, Brandon Butcher, and Lawrence Hunsicker

References

van Houwelingen H, Putter H (2011). Dynamic Prediction in Clinical Survival Analysis. CRC Press.

See Also

cv.ncvsurv(), survival::concordancefit()

Examples

data(Lung)
X <- Lung$X
y <- Lung$y

cvfit <- cv.ncvsurv(X, y, returnY=TRUE)
head(AUC(cvfit))
lam <- cvfit$lambda
plot(lam, AUC(cvfit), xlim=rev(range(lam)), lwd=3, type='l',
     las=1, xlab=expression(lambda), ylab='AUC')

pbreheny/ncvreg documentation built on April 25, 2024, 5:22 a.m.