lt-methods: Create an lt table from a simulation summary

In simtrial: Clinical Trial Simulation

Create an lt table from a simulation summary

Description

S3 method for lt() that converts a group sequential simulation summary (a simtrial_gs_wlr object returned by summary()) into a formatted lt table. This is the lightweight replacement for the deprecated as_gt().

Usage

## S3 method for class 'simtrial_gs_wlr'
lt(
  data,
  title = "Summary of simulation results by WLR tests",
  subtitle = NULL,
  ...
)

Arguments

data	A summary object returned by summary().
title	Title of the lt table.
subtitle	Subtitle of the lt table.
...	Additional arguments (not used).

Value

An lt_tbl object summarizing the simulation results.

See Also

as_gt()

Examples

# Parameters for enrollment
enroll_rampup_duration <- 4 # Duration for enrollment ramp up
enroll_duration <- 16 # Total enrollment duration
enroll_rate <- gsDesign2::define_enroll_rate(
  duration = c(
    enroll_rampup_duration, enroll_duration - enroll_rampup_duration),
 rate = c(10, 30))

# Parameters for treatment effect
delay_effect_duration <- 3 # Delay treatment effect in months
median_ctrl <- 9 # Survival median of the control arm
median_exp <- c(9, 14) # Survival median of the experimental arm
dropout_rate <- 0.001
fail_rate <- gsDesign2::define_fail_rate(
  duration = c(delay_effect_duration, 100),
  fail_rate = log(2) / median_ctrl,
  hr = median_ctrl / median_exp,
  dropout_rate = dropout_rate)

# Other related parameters
alpha <- 0.025 # Type I error
beta <- 0.1 # Type II error
ratio <- 1 # Randomization ratio (experimental:control)

# Build a one-sided group sequential design
design <- gsDesign2::gs_design_ahr(
  enroll_rate = enroll_rate, fail_rate = fail_rate,
  ratio = ratio, alpha = alpha, beta = beta,
  analysis_time = c(12, 24, 36),
  upper = gsDesign2::gs_spending_bound,
  upar = list(sf = gsDesign::sfLDOF, total_spend = alpha),
  lower = gsDesign2::gs_b,
  lpar = rep(-Inf, 3))

# Define cuttings of 2 IAs and 1 FA
ia1_cut <- create_cut(target_event_overall = ceiling(design$analysis$event[1]))
ia2_cut <- create_cut(target_event_overall = ceiling(design$analysis$event[2]))
fa_cut <- create_cut(target_event_overall = ceiling(design$analysis$event[3]))

# Run simulations
simulation <- sim_gs_n(
  n_sim = 3,
  sample_size = ceiling(design$analysis$n[3]),
  enroll_rate = design$enroll_rate,
  fail_rate = design$fail_rate,
  test = wlr,
  cut = list(ia1 = ia1_cut, ia2 = ia2_cut, fa = fa_cut),
  weight = fh(rho = 0, gamma = 0.5))

# Summarize simulations
simulation |>
 summary(bound = gsDesign::gsDesign(k = 3, test.type = 1, sfu = gsDesign::sfLDOF)$upper$bound) |>
 lt()

# Summarize simulations and compare with the planned design
simulation |>
  summary(design = design) |>
  lt()

simtrial documentation built on Sept. 10, 2026, 1:10 a.m.