confint.tp.survtmle: confint.tp.survtmle

In benkeser/survtmle: Compute Targeted Minimum Loss-Based Estimates in Right-Censored Survival Settings

confint.tp.survtmle

Description

Computes confidence intervals for a fitted tp.survtmle object.

Usage

## S3 method for class 'tp.survtmle'
confint(object, parm, level = 0.95, ...)

Arguments

object	An object of class tp.survtmle, as produced by invoking for the function timepoints on an object produced by survtmle, for which a confidence interval is to be computed.
parm	A numeric vector indicating which indexes of object$est to return confidence intervals for (default is to return all). NOT USED NOW.
level	A numeric indicating the level of the confidence interval to be computed.
...	Other arguments. Not currently used.

Value

A list of matrices, each with columns giving the lower and upper confidence limits for each parameter. These will be labeled as (1-level)/2 and 1 - (1-level)/2 in percent. The default is 2.5 contains as many matrices as their are comparison groups in the input data.

Examples

# simulate data
set.seed(1234)
n <- 100
ftime <- round(runif(n, 1, 4))
ftype <- round(runif(n, 0, 2))
trt <- rbinom(n, 1, 0.5)
adjustVars <- data.frame(W1 = rnorm(n), W2 = rnorm(n))

# fit a survtmle object
fit <- survtmle(
  ftime = ftime, ftype = ftype, trt = trt,
  adjustVars = adjustVars, glm.trt = "W1 + W2",
  glm.ftime = "trt + W1 + W2", glm.ctime = "trt + W1 + W2",
  method = "mean", t0 = 4
)
# extract cumulative incidence at each timepoint
tpfit <- timepoints(fit, times = seq_len(4))
# get confidence intervals
ci <- confint(tpfit)
ci

benkeser/survtmle documentation built on Nov. 23, 2023, 4:45 a.m.