simulate.safeDesign: Simulate Early Stopping Experiments for the T Test

Description

Applied to a 'safeDesign' object this function empirically shows the performance of safe experiments under optional stopping.

Usage

# S3 method for safeDesign
simulate(
  object,
  nsim = nSim,
  seed = NULL,
  deltaTrue = NULL,
  muGlobal = 0,
  sigmaTrue = 1,
  lowN = 3,
  safeOptioStop = TRUE,
  freqOptioStop = FALSE,
  nPlanFreq = NULL,
  logging = TRUE,
  pb = TRUE,
  nSim = 1,
  ...
)

Value

Returns an object of class "safeTSim". An object of class "safeTSim" is a list containing at least the following components:

nPlan: the planned sample size(s).

deltaTrue

the value of the true standardised effect size (test-relevant parameter) provided by the user.

muGlobal

the true global mean of a paired or two-sample t-test (nuisance parameter) provided by the user.

paired

if TRUE then paired t-test.

alternative

any of "twoSided", "greater", "less" provided by the user.

lowN

the smallest number of samples (first group) at which monitoring of the tests begins.

nSim

the number of replications of the experiment.

alpha

the tolerable type I error provided by the user.

beta

the tolerable type II error provided by the user.

testType

any of "oneSample", "paired", "twoSample" provided by the user.

parameter

the parameter (point prior) used in the safe test derived from the design. Acquired from designSafeT().

nPlanFreq

the frequentist planned sample size(s). Acquired from designFreqT()

safeSim

list with the simulation results of the safe test under optional stopping.

freqSim

list with the simulation results of the frequentist test under optional stopping.

Arguments

object: A safeDesign obtained obtained from designSafeT().
nsim: integer, formally the number of iterations, but by default nsim=nSim
seed: integer, seed number.
deltaTrue: numeric, if NULL, then the minimally clinically relevant standardised effect size is used as the true data generating effect size deltaTrue.
muGlobal: numeric, the true global mean of a paired or two-sample t-test. Its value should not matter for the test. This parameter is treated as a nuisance.
sigmaTrue: numeric > 0,the true standard deviation of the data. Its value should not matter for the test.This parameter treated is treated as a nuisance.
lowN: integer that defines the smallest n of our search space for n.
safeOptioStop: logical, TRUE implies that optional stopping simulation is performed for the safe test.
freqOptioStop: logical, TRUE implies that optional stopping simulation is performed for the frequentist test.
nPlanFreq: the frequentist sample size(s) to plan for. Acquired from designFreqT().
logging: logical, if TRUE, then return the simulated data.
pb: logical, if TRUE, then show progress bar.
nSim: integer, number of iterations.
...: further arguments to be passed to or from methods.

Examples

Run this code

# Design safe test
alpha <- 0.05
beta <- 0.20
deltaMin <- 1
designObj <- designSafeT(deltaMin, alpha=alpha, beta=beta, nSim=100)

# Design frequentist test
freqObj <- designFreqT(deltaMin, alpha=alpha, beta=beta)

# Simulate based on deltaTrue=deltaMin
simResultsDeltaTrueIsDeltaMin <- simulate(object=designObj, nSim=100)

# Simulate based on deltaTrue > deltaMin
simResultsDeltaTrueIsLargerThanDeltaMin <- simulate(
  object=designObj, nSim=100, deltaTrue=2)

# Simulate under the null deltaTrue = 0
simResultsDeltaTrueIsNull <- simulate(
  object=designObj, nSim=100, deltaTrue=0)

simulate(object=designObj, deltraTrue=0, nSim=100, freqOptioStop=TRUE,
         nPlanFreq=freqObj$nPlan)

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