Nothing
testthat::test_that("Return expected result", {
local_edition(3)
mu_T <- c(AUCinf = 37162.0, AUClast = 35702.0, Cmax = 125.9)
mu_R1 <- c(AUCinf = 37705.0, AUClast = 35930.0, Cmax = 125.1)
mu_R2 <- c(AUCinf = 37702.8, AUClast = 35862.4, Cmax = 126.9)
mu_list <- list("SB2" = mu_T,
"EUREF" = mu_R1,
"USREF" = mu_R2)
# Save variance covariance matrix in a list
sigma_T <- c(AUCinf = 11113.62172, AUClast = 9132.75342, Cmax = 16.89586)
sigma_R1 <- c(AUCinf = 12332.41615, AUClast = 9398.42182, Cmax = 17.88151)
sigma_R2 <- c(AUCinf = 12113.72, AUClast = 9098.42182, Cmax = 17.1586)
sigma_list <- list("SB2" = sigma_T,
"EUREF" = sigma_R1,
"USREF" = sigma_R2)
# Same treatment allocation rate
TAR = c("SB2" = 1, "EUREF" = 1, "USREF" = 1)
# arms to be compared
list_comparator <- list(EMA = c("SB2", "EUREF"),
FDA = c("SB2", "USREF"))
# endpoint to be compared
list_y_comparator <- list(EMA = c("AUCinf", "AUClast", "Cmax"),
FDA = c("AUCinf", "AUClast", "Cmax"))
# Define lower equivalence boundaries for each comparator
list_lequi.tol <- list(
EMA = c(AUCinf = 0.8, AUClast = 0.8, Cmax = 0.8),
FDA = c(AUCinf = 0.8, AUClast = 0.8, Cmax = 0.8)
)
# Define upper equivalence boundaries for each comparator
list_uequi.tol <- list(
EMA = c(AUCinf = 1.25, AUClast = 1.25, Cmax = 1.25),
FDA = c(AUCinf = 1.25, AUClast = 1.25, Cmax = 1.25)
)
# Pass the user parameters into a list of parameters and calculate the sample size
res_cal <- sampleSize(mu_list = mu_list, sigma_list = sigma_list,
power = 0.9, dtype = "parallel", ctype = "ROM",
vareq = T, lognorm = TRUE, k = 3,
list_comparator = list_comparator,
list_y_comparator = list_y_comparator,
list_lequi.tol = list_lequi.tol, list_uequi.tol = list_uequi.tol,
seed = 1234,
ncores = 1)
expect_equal(res_cal$response[["n_total"]], 150, tolerance = 6)
})
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