runMultiSim: runMultiSim

In eniclas/FAIRsimulator: Simulation Platform for the FAIR Trial

Description

Simulate multiple instances of a study, optionally in a parallel fashion.

Usage

runMultiSim(StudyOnjIni, extractProbs = TRUE, iter = 1, ncores = 1,
  strProb = "UnWeightedRandomizationProbabilities", cohortAgeNames = NULL,
  clean = TRUE)

Arguments

StudyOnjIni	An initial FAIRsimulator study object created by createStudy.
extractProbs	Whether to also extract randomization probabilities (in parallel).
iter	The number of studies to simulate.
ncores	The number of cores to use for parallel execution.
...	Other parameters. Typically strProb to specify "UnWeightedRandomizationProbabilities" instead of the default "RandomizationProbabilities".

Value

A list with a list if the simulated FAIRsimulator study objects and, optionally, a data.frame with the randomizaion probabilities.

Examples

## Not run: 
StudyObjIni <- createStudy(latestTimeForNewBirthCohorts=18*30,studyStopTime = 32*30,
nSubjects = c(320,320,320),
randomizationProbabilities = list(rep(0.20,5),rep(0.20,5),rep(0.20,5)),
#minAllocationProbabilities = list(c(0,rep(0,4)),c(0,rep(0,4)),c(0,rep(0,4))),
minAllocationProbabilities = list(c(0.2,rep(0,4)),c(0.2,rep(0,4)),c(0.2,rep(0,4))),
treatments =list(c("SoC-1","TRT-1","TRT-2","TRT-3","TRT-4"),c("SoC-2","TRT-5","TRT-6","TRT-7","TRT-8"),c("SoC-3","TRT-9","TRT-10","TRT-11","TRT-12")),
effSizes = list(c(0,0.05,0.1,0.15,0.25),c(0,0.05,0.1,0.15,0.25),c(0,0.05,0.1,0.15,0.25)),
Recruitmentfunction=function(...) {return(5000)},
minSubjects = 10)

myMultStud <- runMultiSim(StudyOnjIni,iter=10,ncores=2)

## End(Not run)

eniclas/FAIRsimulator documentation built on May 16, 2019, 5:12 a.m.