Convert summary table to a gt object
Usage
as_gt(x, ...)
# S3 method for class 'simtrial_gs_wlr'
as_gt(
x,
title = "Summary of simulation results by WLR tests",
subtitle = NULL,
...
)Arguments
- x
A object returned by
summary().- ...
Additional parameters (not used).
- title
Title of the gt table.
- subtitle
Subtitle of the gt table.
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))
#> Backend uses sequential processing.
#> Loading required package: foreach
#> Loading required package: future
# Summarize simulations
simulation |>
summary(bound = gsDesign::gsDesign(k = 3, test.type = 1, sfu = gsDesign::sfLDOF)$upper$bound) |>
simtrial::as_gt()
Summary of simulation results by WLR tests
Weighted by FH(rho=0, gamma=0.5)
analysis
Time
N
Event
Crossing probability
# Summarize simulations and compare with the planned design
simulation |>
summary(design = design) |>
simtrial::as_gt()
Summary of simulation results by WLR tests
Weighted by FH(rho=0, gamma=0.5)
Asymptotic
Simulated
Asymptotic
Simulated
Asymptotic
Simulated
Asymptotic
Simulated