Nothing
test_that("analyses with interim_posterior work", {
design <- setupTwoStageBasket(k = 3, shape1 = 1, shape2 = 1, p0 = 0.2)
ess1 <- ess(design = design, p1 = c(0.5, 0.2, 0.2), n = 24,
n1 = 15, lambda = 0.99, interim_fun = interim_posterior,
interim_params = list(
prob_futstop = 0.3,
prob_effstop = 0.95
),
weight_fun = weights_fujikawa,
weight_params = list(
epsilon = 2,
tau = 0,
logbase = exp(1)
),
results = "group")
ess2 <- ess(design = design, p1 = c(0.5, 0.2, 0.2), n = 24,
n1 = 15, lambda = 0.99, interim_fun = interim_posterior,
interim_params = list(
prob_futstop = 0.3,
prob_effstop = 0.9
),
weight_fun = weights_fujikawa,
weight_params = list(
epsilon = 2,
tau = 0,
logbase = exp(1)
),
results = "group")
ess3 <- ess(design = design, p1 = c(0.5, 0.2, 0.2), n = 24,
n1 = 15, lambda = 0.99, interim_fun = interim_posterior,
interim_params = list(
prob_futstop = 0.5,
prob_effstop = 0.95
),
weight_fun = weights_fujikawa,
weight_params = list(
epsilon = 2,
tau = 0,
logbase = exp(1)
),
results = "group")
# Expected sample sizes drecrease when boundary for efficacy stop
# is lowered and boundary for futility stop is raised.
expect_true(all(ess1 > ess2))
expect_true(all(ess1 > ess3))
})
test_that("analyses with interim_postpred work", {
design <- setupTwoStageBasket(k = 3, shape1 = 1, shape2 = 1, p0 = 0.2)
ess1 <- ess(design = design, p1 = c(0.5, 0.2, 0.2), n = 24,
n1 = 15, lambda = 0.99, interim_fun = interim_postpred,
interim_params = list(
prob_futstop = 0.1,
prob_effstop = 0.9
),
weight_fun = weights_fujikawa,
weight_params = list(
epsilon = 2,
tau = 0,
logbase = exp(1)
),
results = "group")
ess2 <- ess(design = design, p1 = c(0.5, 0.2, 0.2), n = 24,
n1 = 15, lambda = 0.99, interim_fun = interim_postpred,
interim_params = list(
prob_futstop = 0.1,
prob_effstop = 0.8
),
weight_fun = weights_fujikawa,
weight_params = list(
epsilon = 2,
tau = 0,
logbase = exp(1)
),
results = "group")
ess3 <- ess(design = design, p1 = c(0.5, 0.2, 0.2), n = 24,
n1 = 15, lambda = 0.99, interim_fun = interim_postpred,
interim_params = list(
prob_futstop = 0.3,
prob_effstop = 0.9
),
weight_fun = weights_fujikawa,
weight_params = list(
epsilon = 2,
tau = 0,
logbase = exp(1)
),
results = "group")
# Expected sample sizes drecrease when boundary for efficacy stop
# is lowered and boundary for futility stop is raised.
expect_true(all(ess1 > ess2))
expect_true(all(ess1 > ess3))
})
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