Description Usage Arguments Details Value References See Also Examples

Chambless and Diao's estimator of cumulative/dynamic AUC for right-censored time-to-event data

1 |

`Surv.rsp` |
A |

`Surv.rsp.new` |
A |

`lp` |
The vector of predictors estimated from the training data. |

`lpnew` |
The vector of predictors obtained from the test data. |

`times` |
A vector of time points at which to evaluate AUC. |

This function implements the estimator of cumulative/dynamic AUC proposed in
Section 3.3 of Chambless and Diao (2006). In contrast to the general form of
Chambless and Diao's estimator, `AUC.cd`

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
`AUC.cd`

are valid as long as the Cox model is specified correctly.
The `iauc`

summary measure is given by the integral of AUC on
[0, max(`times`

)] (weighted by the estimated probability density of
the time-to-event outcome).

Note that the recursive estimators proposed in Sections 3.1 and 3.2 of
Chambless and Diao (2006) are not implemented in the **survAUC** package.

`AUC.cd`

returns an object of class `survAUC`

. Specifically,
`AUC.cd`

returns a list with the following components:

`auc` |
The cumulative/dynamic AUC estimates (evaluated at |

`times` |
The vector of time points at which AUC is evaluated. |

`iauc` |
The summary measure of AUC. |

Chambless, L. E. and G. Diao (2006).

Estimation of time-dependent area under
the ROC curve for long-term risk prediction.

*Statistics in Medicine*
**25**, 3474–3486.

`AUC.uno`

, `AUC.sh`

, `AUC.hc`

,
`IntAUC`

1 2 3 4 5 6 7 8 9 10 11 12 | ```
TR <- ovarian[1:16,]
TE <- ovarian[17:26,]
train.fit <- coxph(Surv(futime, fustat) ~ age,
x=TRUE, y=TRUE, method="breslow", data=TR)
lp <- predict(train.fit)
lpnew <- predict(train.fit, newdata=TE)
Surv.rsp <- Surv(TR$futime, TR$fustat)
Surv.rsp.new <- Surv(TE$futime, TE$fustat)
times <- seq(10, 1000, 10)
AUC_CD <- AUC.cd(Surv.rsp, Surv.rsp.new, lp, lpnew, times)
``` |

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