timeroc_gof {parTimeROC}

timeroc_gof

Description

Function to compute goodness-of-fit for the Proportional Hazard (PH) or copula model. For PH model, the Cox-Snell residuals are computed and compared with Exponential(rate=1). For copula model, the Rosenblatt transformation is applied before performing independence testing. Kolmogorov-Smirnov test is performed to check the goodness-of-fit of the biomarker and time-to-event.

Usage

timeroc_gof(obj)

Arguments

obj

A 'fitTROC' object returned from fitting procedure.

Value

A list of test statistics and p-values. Automatically plot residuals for biomarker and time-to-event.

Examples

# Copula model
rt <- timeroc_obj("normal-weibull-copula",copula="clayton90")
set.seed(1)
rr <- rtimeroc(rt, n=300, censor.rate = 0,
               params.x = c(mean=5, sd=1),
               params.t = c(shape=1, scale=5),
               params.copula = -2.5)
plot(t~x, data=rr)
test <- timeroc_obj("normal-weibull-copula",copula="gumbel90")
jj <- timeroc_fit(test, rr$x, rr$t, rr$event)

cc <- timeroc_gof(jj)

test <- timeroc_obj("normal-weibull-copula",copula="clayton90")
jj <- timeroc_fit(test, rr$x, rr$t, rr$event)

cc <- timeroc_gof(jj)

# PH model
rt <- timeroc_obj("normal-weibull-PH")
set.seed(1)
rr <- rtimeroc(rt, n=300, censor.rate = 0,
               params.x = c(mean=5, sd=1),
               params.t = c(shape=1, scale=5),
               params.ph = 1.2)
plot(t~x, data=rr)
test <- timeroc_obj("lognormal-lognormal-PH")
jj <- timeroc_fit(test, rr$x, rr$t, rr$event)

cc <- timeroc_gof(jj)

test <- timeroc_obj("normal-weibull-PH")
jj <- timeroc_fit(test, rr$x, rr$t, rr$event)

cc <- timeroc_gof(jj)