validation/test_code/05_MultipleTestCode.R
In Sterniii3/drugdevelopR: Utility-Based Optimal Phase II/III Drug Development Planning
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.01", {
# Multiple time-to-event endpoints (run time approx. 1 day)
set.seed(123)
res <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = FALSE,
)
expect_equal(res$u, -212.24, tolerance = 0.005)
expect_equal(res$n2, 100)
expect_equal(res$n3, 262)
expect_equal(res$n, 362)
expect_equal(res$HRgo, 0.88)
expect_equal(res$pgo, 0.74)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.02", {
# Multiple time-to-event endpoints with sample size constraint
# (run time approx. 1 day)
set.seed(123)
res <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.9, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = FALSE,
N = 330
)
expect_equal(res$u, -218.92, tolerance = 0.005)
expect_equal(res$n2, 100)
expect_equal(res$n3, 219)
expect_equal(res$n, 319)
expect_equal(res$HRgo, 0.86)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.03", {
# Multiple time-to-event endpoints -- no cost limit (duration: several seconds)
set.seed(123)
res_nolim <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = TRUE,
)
# With cost limit
res_lim <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = TRUE,
K = 600
)
expect_equal(res_nolim$u, 144.96, tolerance = 0.005)
expect_equal(res_nolim$n2, 172)
expect_equal(res_nolim$n3, 408)
expect_equal(res_nolim$n, 580)
expect_equal(res_nolim$HRgo, 0.86)
expect_equal(res_nolim$K2, 229)
expect_equal(res_nolim$K3, 532)
expect_equal(res_lim$u, 130.67, tolerance = 0.005)
expect_equal(res_lim$n2, 112)
expect_equal(res_lim$n3, 301)
expect_equal(res_lim$n, 413)
expect_equal(res_lim$HRgo, 0.84)
expect_equal(res_lim$K2, 184)
expect_equal(res_lim$K3, 414)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.04", {
# Multiple time-to-event endpoints (duration: several seconds)
set.seed(123)
res <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = TRUE,
S = 0.6
)
expect_equal(res$u, 132.6, tolerance = 0.005)
expect_equal(res$n2, 280)
expect_equal(res$n3, 467)
expect_equal(res$n, 747)
expect_equal(res$HRgo, 0.86)
expect_equal(res$sProg, 0.6)
expect_equal(res$OS, 0.54)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.05", {
# Multiple time-to-event endpoints (duration: approx. one day)
start_time_3 = Sys.time()
set.seed(123)
optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 200, n2max = 300, stepn2 = 4,
hrgomin = 0.86, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = FALSE,
)
end_time_3 = Sys.time()
time_elapsed_num_cl_3 = end_time_3 - start_time_3
start_time_1 = Sys.time()
optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 200, n2max = 300, stepn2 = 4,
hrgomin = 0.86, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 6,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = FALSE,
)
end_time_1 = Sys.time()
time_elapsed_num_cl_1 = end_time_1 - start_time_1
expect_true(time_elapsed_num_cl_1 > time_elapsed_num_cl_3)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.06", {
# Multiple normally distributed endpoints -- no sample size constraint
# (Duration: approx. one day)
set.seed(123)
res_nolim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
expect_equal(res_nolim$u, 1476.09, tolerance = 0.005)
expect_equal(res_nolim$n2, 144)
expect_equal(res_nolim$n3, 78)
expect_equal(res_nolim$n, 222)
expect_equal(res_nolim$Kappa, 0.02)
# Multiple normally distributed endpoints -- with sample size constraint
res_lim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE,
N = 190,
)
expect_equal(res_lim$u, 809.23, tolerance = 0.005)
expect_equal(res_lim$n2, 92)
expect_equal(res_lim$n3, 97)
expect_equal(res_lim$n, 189)
expect_equal(res_lim$Kappa, 0.08)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.07", {
# Multiple normally distributed endpoints -- parallel computing
# (Duration: approx. one day)
start_time_3 = Sys.time()
set.seed(123)
optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.04, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
end_time_3 = Sys.time()
time_elapsed_num_cl_3 = end_time_3 - start_time_3
start_time_1 = Sys.time()
optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.04, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 6,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
end_time_1 = Sys.time()
time_elapsed_num_cl_1 = end_time_1 - start_time_1
expect_true(time_elapsed_num_cl_1 > time_elapsed_num_cl_3)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.08", {
# Multiple normally distributed endpoints -- with and without cost limit
# Duration approx. 1 hour
set.seed(123)
res_nolim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
res_lim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE,
K = 400
)
expect_equal(res_nolim$u, 1133, tolerance = 0.005)
expect_equal(res_nolim$n2, 160)
expect_equal(res_nolim$K2, 220)
expect_equal(res_nolim$K3, 215)
expect_equal(res_nolim$Kappa, 0.02)
expect_equal(res_lim$u, 1099, tolerance = 0.005)
expect_equal(res_lim$n2, 104)
expect_equal(res_lim$K2, 178)
expect_equal(res_lim$K3, 220)
expect_equal(res_lim$Kappa, 0.02)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.09", {
# Multiple normally distributed endpoints
# -- constraint on success probability
# Duration several minutes
set.seed(123)
res_nolim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
res_lim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE,
S = 0.85
)
expect_equal(res_nolim$u, 1133, tolerance = 0.005)
expect_equal(res_nolim$n2, 160)
expect_equal(res_nolim$sProg, 0.835)
expect_equal(res_nolim$sProg1, 0.15)
expect_equal(res_nolim$sProg2, 0.637)
expect_equal(res_nolim$sProg3, 0.048)
expect_equal(res_nolim$Kappa, 0.02)
expect_equal(res_lim$u, -9999, tolerance = 0.005)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.10", {
# Multiple normally distributed endpoints
# -- relaxed and strict rule
# Duration several minutes
set.seed(123)
res_relax <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
res_strict <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = FALSE,
)
expect_equal(res_relax$u, 1133, tolerance = 0.005)
expect_equal(res_relax$n2, 160)
expect_equal(res_relax$Kappa, 0.02)
expect_equal(res_relax$pgo, 0.99)
expect_equal(res_strict$u, 410, tolerance = 0.005)
expect_equal(res_strict$n2, 132)
expect_equal(res_strict$Kappa, 0.02)
expect_equal(res_strict$pgo, 0.98)
})
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#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.01", {
# Multiple time-to-event endpoints (run time approx. 1 day)
set.seed(123)
res <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = FALSE,
)
expect_equal(res$u, -212.24, tolerance = 0.005)
expect_equal(res$n2, 100)
expect_equal(res$n3, 262)
expect_equal(res$n, 362)
expect_equal(res$HRgo, 0.88)
expect_equal(res$pgo, 0.74)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.02", {
# Multiple time-to-event endpoints with sample size constraint
# (run time approx. 1 day)
set.seed(123)
res <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.9, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = FALSE,
N = 330
)
expect_equal(res$u, -218.92, tolerance = 0.005)
expect_equal(res$n2, 100)
expect_equal(res$n3, 219)
expect_equal(res$n, 319)
expect_equal(res$HRgo, 0.86)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.03", {
# Multiple time-to-event endpoints -- no cost limit (duration: several seconds)
set.seed(123)
res_nolim <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = TRUE,
)
# With cost limit
res_lim <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = TRUE,
K = 600
)
expect_equal(res_nolim$u, 144.96, tolerance = 0.005)
expect_equal(res_nolim$n2, 172)
expect_equal(res_nolim$n3, 408)
expect_equal(res_nolim$n, 580)
expect_equal(res_nolim$HRgo, 0.86)
expect_equal(res_nolim$K2, 229)
expect_equal(res_nolim$K3, 532)
expect_equal(res_lim$u, 130.67, tolerance = 0.005)
expect_equal(res_lim$n2, 112)
expect_equal(res_lim$n3, 301)
expect_equal(res_lim$n, 413)
expect_equal(res_lim$HRgo, 0.84)
expect_equal(res_lim$K2, 184)
expect_equal(res_lim$K3, 414)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.04", {
# Multiple time-to-event endpoints (duration: several seconds)
set.seed(123)
res <- optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 100, n2max = 300, stepn2 = 4,
hrgomin = 0.80, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = TRUE,
S = 0.6
)
expect_equal(res$u, 132.6, tolerance = 0.005)
expect_equal(res$n2, 280)
expect_equal(res$n3, 467)
expect_equal(res$n, 747)
expect_equal(res$HRgo, 0.86)
expect_equal(res$sProg, 0.6)
expect_equal(res$OS, 0.54)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.05", {
# Multiple time-to-event endpoints (duration: approx. one day)
start_time_3 = Sys.time()
set.seed(123)
optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 200, n2max = 300, stepn2 = 4,
hrgomin = 0.86, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = FALSE,
)
end_time_3 = Sys.time()
time_elapsed_num_cl_3 = end_time_3 - start_time_3
start_time_1 = Sys.time()
optimal_multiple_tte(alpha = 0.025,
beta = 0.1,
hr1 = 0.75, hr2 = 0.85,
id1 = 210, id2 = 420,
n2min = 200, n2max = 300, stepn2 = 4,
hrgomin = 0.86, hrgomax = 0.90, stephrgo = 0.02,
steps1 = 1, stepm1 = 0.95, stepl1 = 0.85,
b11 = 1000, b21 = 1500, b31 = 2000,
b12 = 1000, b22 = 2000, b32 = 3000,
num_cl = 6,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
rho = 0.6,
fixed = FALSE,
)
end_time_1 = Sys.time()
time_elapsed_num_cl_1 = end_time_1 - start_time_1
expect_true(time_elapsed_num_cl_1 > time_elapsed_num_cl_3)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.06", {
# Multiple normally distributed endpoints -- no sample size constraint
# (Duration: approx. one day)
set.seed(123)
res_nolim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
expect_equal(res_nolim$u, 1476.09, tolerance = 0.005)
expect_equal(res_nolim$n2, 144)
expect_equal(res_nolim$n3, 78)
expect_equal(res_nolim$n, 222)
expect_equal(res_nolim$Kappa, 0.02)
# Multiple normally distributed endpoints -- with sample size constraint
res_lim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE,
N = 190,
)
expect_equal(res_lim$u, 809.23, tolerance = 0.005)
expect_equal(res_lim$n2, 92)
expect_equal(res_lim$n3, 97)
expect_equal(res_lim$n, 189)
expect_equal(res_lim$Kappa, 0.08)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.07", {
# Multiple normally distributed endpoints -- parallel computing
# (Duration: approx. one day)
start_time_3 = Sys.time()
set.seed(123)
optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.04, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
end_time_3 = Sys.time()
time_elapsed_num_cl_3 = end_time_3 - start_time_3
start_time_1 = Sys.time()
optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.04, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 6,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = FALSE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
end_time_1 = Sys.time()
time_elapsed_num_cl_1 = end_time_1 - start_time_1
expect_true(time_elapsed_num_cl_1 > time_elapsed_num_cl_3)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.08", {
# Multiple normally distributed endpoints -- with and without cost limit
# Duration approx. 1 hour
set.seed(123)
res_nolim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
res_lim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE,
K = 400
)
expect_equal(res_nolim$u, 1133, tolerance = 0.005)
expect_equal(res_nolim$n2, 160)
expect_equal(res_nolim$K2, 220)
expect_equal(res_nolim$K3, 215)
expect_equal(res_nolim$Kappa, 0.02)
expect_equal(res_lim$u, 1099, tolerance = 0.005)
expect_equal(res_lim$n2, 104)
expect_equal(res_lim$K2, 178)
expect_equal(res_lim$K3, 220)
expect_equal(res_lim$Kappa, 0.02)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.09", {
# Multiple normally distributed endpoints
# -- constraint on success probability
# Duration several minutes
set.seed(123)
res_nolim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
res_lim <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE,
S = 0.85
)
expect_equal(res_nolim$u, 1133, tolerance = 0.005)
expect_equal(res_nolim$n2, 160)
expect_equal(res_nolim$sProg, 0.835)
expect_equal(res_nolim$sProg1, 0.15)
expect_equal(res_nolim$sProg2, 0.637)
expect_equal(res_nolim$sProg3, 0.048)
expect_equal(res_nolim$Kappa, 0.02)
expect_equal(res_lim$u, -9999, tolerance = 0.005)
})
#' @editor Lukas D Sauer
#' @editDate 2022-12-29
test_that("05.10", {
# Multiple normally distributed endpoints
# -- relaxed and strict rule
# Duration several minutes
set.seed(123)
res_relax <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = TRUE
)
res_strict <- optimal_multiple_normal(alpha = 0.05,
beta = 0.1,
Delta1 = 0.75, Delta2 = 0.8,
n2min = 80, n2max = 160, stepn2 = 4,
kappamin = 0.02, kappamax = 0.1, stepkappa = 0.02,
b1 = 1000, b2 = 2000, b3 = 3000,
num_cl = 12,
c02 = 100, c03 = 150,
c2 = 0.75, c3 = 1,
fixed = TRUE,
rho = 0.5,
sigma1 = 2, sigma2 = 1,
in1 = 300, in2 = 600,
relaxed = FALSE,
)
expect_equal(res_relax$u, 1133, tolerance = 0.005)
expect_equal(res_relax$n2, 160)
expect_equal(res_relax$Kappa, 0.02)
expect_equal(res_relax$pgo, 0.99)
expect_equal(res_strict$u, 410, tolerance = 0.005)
expect_equal(res_strict$n2, 132)
expect_equal(res_strict$Kappa, 0.02)
expect_equal(res_strict$pgo, 0.98)
})
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