tdroc: Calculate tdROC

In csetraynor/iclust2prog: Prognostic modeling of IntClust-2 (iclust2prog)

Description

The time dependent ROC analysis (tdROC) allows the user to visualise the sensitivity (true positive rate) and specificity (false positive rate) for all possible cut-offs for the predicted survival. #'

Usage

tdroc(data, mod, ...)

get_tdroc(data, mod, ...)

integrate_tdroc(mod, ...)

Arguments

data	For the default functions, a datframe containing survival (time), and status (0:censored/1:event), and the explanatory variables.
mod	Coxph model object fitted with coxph (survival).

Value

A tdROC object

Author(s)

Carlos S Traynor

References

Liang Li, Cai Wu Department of Biostatistics and The University of Texas MD Anderson Cancer Center (2016). tdROC: Nonparametric Estimation of Time-Dependent ROC Curve from Right Censored Survival Data. R package version 1.0. https://CRAN.R-project.org/package=tdROC

See Also

[iROC]

Examples

require(survival)
require(dplyr)
data(lung)
lung <- lung %>%
mutate(status = (status == 2))

mod <- coxph(Surv(time, status)~ age, data = lung)

tdroc <- get_tdroc(lung, mod)
integrate_tdroc(tdroc)

csetraynor/iclust2prog documentation built on May 7, 2019, 8:38 a.m.