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delete helper-sim_gs_n.R
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@LittleBeannie
LittleBeannie committed Aug 1, 2024
1 parent 98ccfd7 commit e46c6ba
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74 changes: 0 additions & 74 deletions tests/testthat/helper-sim_gs_n.R
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143 changes: 106 additions & 37 deletions tests/testthat/test-unvalidated-sim_gs_n.R
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Original file line number Diff line number Diff line change
@@ -1,17 +1,86 @@
# 2024-02-22: Converted `example("sim_gs_n")` to tests from commit 306de0d
# https://github.com/Merck/simtrial/tree/306de0dbe380fdb1e906a59f34bf3871d3ee5312

# See helper-sim_gs_n.R for helper functions
# 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 (exp:ctrl)
# Define cuttings of 2 IAs and 1 FA
# IA1
# The 1st interim analysis will occur at the later of the following 3 conditions:
# - At least 20 months have passed since the start of the study
# - At least 100 events have occurred
# - At least 20 months have elapsed after enrolling 200/400 subjects, with a
# minimum of 20 months follow-up
# However, if events accumulation is slow, we will wait for a maximum of 24 months.
ia1_cut <- create_cut(
planned_calendar_time = 20,
target_event_overall = 100,
max_extension_for_target_event = 24,
min_n_overall = 200,
min_followup = 20
)

# IA2
# The 2nd interim analysis will occur at the later of the following 3 conditions:
# - At least 32 months have passed since the start of the study
# - At least 250 events have occurred
# - At least 10 months after IA1
# However, if events accumulation is slow, we will wait for a maximum of 34 months.
ia2_cut <- create_cut(
planned_calendar_time = 32,
target_event_overall = 200,
max_extension_for_target_event = 34,
min_time_after_previous_analysis = 10
)

# FA
# The final analysis will occur at the later of the following 2 conditions:
# - At least 45 months have passed since the start of the study
# - At least 300 events have occurred
fa_cut <- create_cut(
planned_calendar_time = 45,
target_event_overall = 350
)

cut <- list(ia1 = ia1_cut, ia2 = ia2_cut, fa = fa_cut)


test_that("regular logrank test", {
set.seed(2024)
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = wlr,
cut = test_cutting(),
cut = cut,
weight = fh(rho = 0, gamma = 0)
)
expected <- data.frame(
Expand Down Expand Up @@ -47,10 +116,10 @@ test_that("regular logrank test parallel", {
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = wlr,
cut = test_cutting(),
cut = cut,
weight = fh(rho = 0, gamma = 0)
)
plan("sequential")
Expand Down Expand Up @@ -87,10 +156,10 @@ test_that("weighted logrank test by FH(0, 0.5)", {
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = wlr,
cut = test_cutting(),
cut = cut,
weight = fh(rho = 0, gamma = 0.5)
)
expected <- data.frame(
Expand Down Expand Up @@ -125,10 +194,10 @@ test_that("weighted logrank test by MB(3)", {
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = wlr,
cut = test_cutting(),
cut = cut,
weight = mb(delay = 3)
)
expected <- data.frame(
Expand Down Expand Up @@ -163,10 +232,10 @@ test_that("weighted logrank test by early zero (6)", {
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = wlr,
cut = test_cutting(),
cut = cut,
weight = early_zero(6)
)
expected <- data.frame(
Expand Down Expand Up @@ -201,10 +270,10 @@ test_that("RMST", {
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = rmst,
cut = test_cutting(),
cut = cut,
tau = 20
)
expected <- data.frame(
Expand Down Expand Up @@ -239,10 +308,10 @@ test_that("Milestone", {
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = milestone,
cut = test_cutting(),
cut = cut,
ms_time = 10,
test_type = "naive"
)
Expand Down Expand Up @@ -282,10 +351,10 @@ test_that("WLR with fh(0, 0.5) test at IA1, WLR with mb(6, Inf) at IA2, and mile
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = list(ia1 = ia1_test, ia2 = ia2_test, fa = fa_test),
cut = test_cutting()
cut = cut
)
expected <- data.frame(
sim_id = rep(1:3, each = 3L),
Expand Down Expand Up @@ -319,10 +388,10 @@ test_that("MaxCombo (WLR-FH(0,0) + WLR-FH(0, 0.5))", {
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = maxcombo,
cut = test_cutting(),
cut = cut,
rho = c(0, 0),
gamma = c(0, 0.5)
)
Expand Down Expand Up @@ -363,10 +432,10 @@ test_that("sim_gs_n() accepts different tests per cutting", {
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = list(wlr_cut1, wlr_cut2, wlr_cut3),
cut = test_cutting()
cut = cut
)
expected <- data.frame(
sim_id = rep(1:3, each = 3L),
Expand Down Expand Up @@ -406,10 +475,10 @@ test_that("sim_gs_n() requires a test for each cutting", {
sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = list(wlr_cut1, wlr_cut2),
cut = test_cutting()
cut = cut
),
"If you want to run different tests at each cutting"
)
Expand All @@ -424,10 +493,10 @@ test_that("sim_gs_n() can combine wlr(), rmst(), and milestone() tests", {
observed <- sim_gs_n(
n_sim = 3,
sample_size = 400,
enroll_rate = test_enroll_rate(),
fail_rate = test_fail_rate(),
enroll_rate = enroll_rate,
fail_rate = fail_rate,
test = list(test_cut1, test_cut2, test_cut3),
cut = test_cutting()
cut = cut
)
expected <- data.frame(
sim_id = rep(1:3, each = 3L),
Expand Down

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