View source: R/surv_measures.R

OXS | R Documentation |

R2-type Coefficients for Cox proportional hazards models

```
OXS(Surv.rsp, lp, lp0)
Nagelk(Surv.rsp, lp, lp0)
XO(Surv.rsp, lp, lp0)
```

`Surv.rsp` |
A |

`lp` |
The vector of predictors. |

`lp0` |
The vector of predictors obtained from the covariate-free null model. |

The `OXS`

, `Nagelk`

and `XO`

functions implement three types of R2 coefficients for right-censored
time-to-event data: (a) The coefficient proposed by O'Quigley et al. (2005) (`OXS`

), (b)
the coefficient proposed by Nagelkerke (1991) (`Nagelk`

) and (c) the
coefficient proposed by Xu and O'Quigley (1999) (`XO`

).

Because the `OXS`

, `Nagelk`

and `XO`

functions assume that `lp`

and `lpnew`

were
derived from a correctly specified Cox proportional hazards model, estimates obtained from these functions are only
valid if the Cox model holds.

The estimated R2 coefficient.

Nagelkerke, N. J. D. (1991).

A note on a general definition of the coefficient of
determination.

*Biometrika* **78**, 691–692.

O'Quigley, J., R. Xu, and J. Stare (2005).

Explained randomness in proportional
hazards models.

*Statistics in Medicine* **24**, 479–489.

Xu, R. and J. O'Quigley (1999).

A measure of dependence for proportional
hazards models.

*Journal of Nonparametric Statistics* **12**, 83–107.

`predErr`

, `schemper`

, `GHCI`

```
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)
model0 <- survival::coxph(survival::Surv(futime, fustat)~1, data=TR)
model1 <- survival::coxph(survival::Surv(futime, fustat)~age, data=TR)
f0 <- rep(0,nrow(TE))
f1 <- predict(model1, newdata=TE)
Surv.res <- survival::Surv(TE$futime, TE$fustat)
OXS(Surv.res, f1, f0)
Nagelk(Surv.res, f1, f0)
XO(Surv.res, f1, f0)
```

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