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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