milestone: Milestone test for two survival curves

In Merck/simtrial: Clinical Trial Simulation

Milestone test for two survival curves

Description

Milestone test for two survival curves

Usage

milestone(data, ms_time, test_type = c("log-log", "naive"))

Arguments

data	Data frame containing at least 3 columns: tte - Time to event. event - Event indicator. treatment - Grouping variable.
ms_time	Milestone analysis time.
test_type	Method to build the test statistics. There are 2 options: "native": a native approach by dividing the KM survival difference by its standard derivations, see equation (1) of Klein, J. P., Logan, B., Harhoff, M., & Andersen, P. K. (2007). "log-log": a log-log transformation of the survival, see equation (3) of Klein, J. P., Logan, B., Harhoff, M., & Andersen, P. K. (2007).

Value

A list frame containing:

• method - The method, always "milestone".

• parameter - Milestone time point.

• estimate - Survival difference between the experimental and control arm.

• se - Standard error of the control and experimental arm.

• z - Test statistics.

References

Klein, J. P., Logan, B., Harhoff, M., & Andersen, P. K. (2007). "Analyzing survival curves at a fixed point in time." Statistics in Medicine, 26(24), 4505–4519.

Examples

cut_data <- sim_pw_surv(n = 200) |>
  cut_data_by_event(150)

cut_data |>
  milestone(10, test_type = "log-log")

cut_data |>
  milestone(10, test_type = "naive")

Merck/simtrial documentation built on April 14, 2025, 5:37 a.m.