View source: R/simulate_pite.R
simulate_pite | R Documentation |
This function runs simulations of the PRINTE design by evaluating operating characteristics over a range of cohort sizes. For each dose level within the user-specified range, it performs multiple trials and saves the results to a corresponding file.
simulate_pite(
ndose,
ssizerange,
target_t,
target_e,
lower_e,
cohortsize = 3,
startdose = 1,
eps1 = 0.05,
eps2 = 0.05,
psafe = 0.95,
pfutility = 0.9,
ntrial = 10000,
utilitytype = 1,
u1,
u2,
prob = NULL,
save_dir = tempdir(),
save_folder = "pite_simulations",
save_file = "pite_simulation.csv"
)
ndose |
Integer. Number of dose levels. (Required) |
ssizerange |
Integer vector. Range of number of cohorts to simulate. (Required) |
target_t |
Numeric. Target toxicity probability. (Required) |
target_e |
Numeric. Target efficacy probability. (Required) |
lower_e |
Numeric. Minimum acceptable efficacy probability. (Required) |
cohortsize |
Integer. Size of a cohort. (Default is |
startdose |
Integer. Starting dose level. (Default is |
eps1 |
Numerical. Width of the subrectangle. |
eps2 |
Numerical. Width of the subreactangle. |
psafe |
Numeric. Early stopping cutoff for toxicity. (Default is |
pfutility |
Numeric. Early stopping cutoff for efficacy. (Default is |
ntrial |
Integer. Number of random trial replications. (Default is |
utilitytype |
Integer. Type of utility structure. (Default is
|
u1 |
Numeric. Utility parameter w_11. (0-100) |
u2 |
Numeric. Utility parameter w_00. (0-100) |
prob |
Fixed probability vectors. If not specified, a random scenario is used by default. Use this parameter to provide fixed probability vectors as a list with the following named elements:
For example: prob <- list( pE = c(0.4, 0.5, 0.6, 0.6, 0.6), pT = c(0.1, 0.2, 0.3, 0.4, 0.4), obd = 3, mtd = 2 ) |
save_dir |
Directory to save output folders. Default is |
save_folder |
Folder name. (Default is "boin12_simulations") |
save_file |
File name. (Default is "boin12_simulation.csv") |
No return value, called for side effects
prob <- list(
pE = c(0.4, 0.5, 0.6, 0.6, 0.6),
pT = c(0.1, 0.2, 0.3, 0.4, 0.4),
obd = 3,
mtd = 2
)
simulate_pite(
ndose = 5,
ssizerange = 1:2,
target_t = 0.3,
target_e = 0.5,
lower_e = 0.4,
ntrial = 10,
prob = prob,
)
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