BuyseTTEM {BuyseTest}

Time to Event Model

Description

Pre-compute quantities of a time to event model useful for predictions. Only does something for prodlim objects.

Usage

BuyseTTEM(object, ...)

## S3 method for class 'formula'
BuyseTTEM(object, treatment, iid, iid.surv = "exp", ...)

## S3 method for class 'prodlim'
BuyseTTEM(object, treatment, iid, iid.surv = "exp", ...)

## S3 method for class 'survreg'
BuyseTTEM(object, treatment, n.grid = 1000, iid, ...)

## S3 method for class 'BuyseTTEM'
BuyseTTEM(object, ...)

Arguments

object

time to event model.

...

additional arguments passed to lower lever methods.

treatment

[character] Name of the treatment variable.

iid

[logical] Should the iid decomposition of the predictions be output.

iid.surv

[character] Estimator of the survival used when computing the influence function. Can be the product limit estimator ("prodlim") or an exponential approximation ("exp", same as in riskRegression::predictCoxPL).

n.grid

[integer, >0] Number of timepoints used to discretize the time scale. Not relevant for prodlim objects.

Value

An S3 object of class BuyseTTEM.

Examples

library(prodlim)
library(data.table)

tau <- seq(0,3,length.out=10)

#### survival case ####
set.seed(10)
df.data <- simBuyseTest(1e2, n.strata = 2)

e.prodlim <- prodlim(Hist(eventtime,status)~treatment+strata, data = df.data)
## plot(e.prodlim)

e.prodlim2 <- BuyseTTEM(e.prodlim, treatment = "treatment", iid = TRUE)

predict(e.prodlim2, time = tau, treatment = "T", strata = "a")
predict(e.prodlim, times = tau, newdata = data.frame(treatment = "T", strata = "a"))

predict(e.prodlim2, time = tau, treatment = "C", strata = "a")
predict(e.prodlim, times = tau, newdata = data.frame(treatment = "C", strata = "a"))

#### competing risk case ####
df.dataCR <- copy(df.data)
df.dataCR$status <- rbinom(NROW(df.dataCR), prob = 0.5, size = 2)

e.prodlimCR <- prodlim(Hist(eventtime,status)~treatment+strata, data = df.dataCR)
## plot(e.prodlimCR)

e.prodlimCR2 <- BuyseTTEM(e.prodlimCR, treatment = "treatment", iid = TRUE)

predict(e.prodlimCR2, time = tau, treatment = "T", strata = "a")
predict(e.prodlimCR, times = tau, newdata = data.frame(treatment = "T", strata = "a"), cause = 1)

predict(e.prodlimCR2, time = tau, treatment = "C", strata = "a")
predict(e.prodlimCR, times = tau, newdata = data.frame(treatment = "C", strata = "a"), cause = 1)