Learn R Programming

survAUC (version 1.3-0)

BeggC: C-statistic by Begg et al.

Description

C-statistic by Begg et al.

Usage

BeggC(Surv.rsp, Surv.rsp.new, lp, lpnew)

Value

The estimated C-statistic.

Arguments

Surv.rsp

A Surv(.,.) object containing to the outcome of the training data.

Surv.rsp.new

A Surv(.,.) object containing the outcome of the test data.

lp

The vector of predictors estimated from the training data.

lpnew

The vector of predictors obtained from the test data.

Details

This function implements the C-statistic proposed by Begg et al. (2000). It has the same interpretation as Harrell's C for survival data (implemented in the rcorr.cens function of the Hmisc package). BeggC is restricted to Cox regression. Specifically, it is assumed that lp and lpnew are the predictors of a Cox proportional hazards model. Estimates obtained from BeggC are valid as long as the Cox model is specified correctly.

References

Begg, B. C., L. D. Craemer, E. S. Venkatraman and J. Rosai (2000).
Comparing tumor staging and grading systems: a case study and a review of the issues, using thymoma as a model.
Statistics in Medicine 19, 1997--2014.

See Also

UnoC, GHCI, AUC.sh, IntAUC

Examples

Run this code
data(cancer,package="survival")
TR <- ovarian[1:16,]
TE <- ovarian[17:26,]
train.fit  <- survival::coxph(survival::Surv(futime, fustat) ~ age,
                    x=TRUE, y=TRUE, method="breslow", data=TR)

lp <- predict(train.fit)
lpnew <- predict(train.fit, newdata=TE)
Surv.rsp <- survival::Surv(TR$futime, TR$fustat)
Surv.rsp.new <- survival::Surv(TE$futime, TE$fustat)              

Cstat <- BeggC(Surv.rsp, Surv.rsp.new, lp, lpnew)
Cstat

Run the code above in your browser using DataLab