SimulateSimonDsgn: Simon's designs data simulation

In arsenionhacolo/InferenceBEAGSD: Inference for Binary Endpoint Adaptive Group-Sequential Designs

Description

SimulateSimonDsgn simulates data from Simon's optimal and minimax designs.

Usage

SimulateSimonDsgn(replicates, designParam, newp1 = NA, seed = NA,
  deleteOld = TRUE)

Arguments

replicates	Number of trials to be generated.
designParam	A dataframe containing Simon's optimal and minimax designs, as returned by the function CalculateSimonDsgn.
newp1	If NA (default) data are generated assuming the same response probability under alternative hypothesis, p1, used to get the designs (see CalculateSimonDsgn). One may provide different values of newp1 if there is interest in studying the effect of departure from the design's assumed p1.
seed	Initial value (any integer) of random-number seed. It is useful for creating simulations that can be reproduced. The default is NA, meaning no reproducibility.
deleteOld	If TRUE (default) the sub-directories /Optimal/SimulatedTrials and /Minimax/SimulatedTrials are deleted, if they exist, before simulation starts. The old data files are still replaced by the new ones even if deleteOld is set to FALSE, but some old files remain in cases where the previous replicates was greater that the current one.

Details

The simulated trials are stored in the sub-directories /Optimal/SimulatedTrials and /Minimax/SimulatedTrials for optimal and minimax designs, repectively, under the current working directory. The sub-directories are automatically created. Individual trial data are stored in a CSV file named trial#, where # is the replicate number.

Value

The function is not intended to return an R object, instead it creates files (in CSV format) containing simulated trials data. See Details. It also saves in the current working directory the designParam argument (DesignParameters.csv).

Author(s)

Arsenio Nhacolo

See Also

CalculateSimonDsgn, SimulateSimonDsgnAdaptN and AnalyzeSimonDsgn.

Examples

d <- CalculateSimonDsgn(0.2, 0.4, 0.05, 0.1)
SimulateSimonDsgn(100, d, seed = 1986)

arsenionhacolo/InferenceBEAGSD documentation built on May 9, 2019, 4:10 a.m.