EvidenceSynthesis (version 1.0.0)

createSccsSimulationSettings: Create SCCS simulation settings

Description

Create an object specifying a simulation for the Self-Controlled Case Series (SCCS).

Usage

createSccsSimulationSettings(
  nSites = 5,
  n = 10000,
  atRiskTimeFraction = 0.1,
  timePartitions = 24,
  timeCovariates = 5,
  timeEffectSize = log(2),
  minBackgroundRate = 0.001,
  maxBackgroundRate = 0.01,
  rateRatio = 2,
  randomEffectSd = 0
)

Value

An object of type simulationSccsSettings, to be used in the simulatePopulations() function.

Arguments

nSites

Number of database sites to simulate.

n

Number of subjects per site. Either a single number, or a vector of length nSites.

atRiskTimeFraction

Fraction of patient time when at risk (exposed). Either a single number, or a vector of length nSites.

timePartitions

Number of time partitions for seasonal covariates. Either a single number, or a vector of length nSites.

timeCovariates

Number of covariates to represent seasonality. Either a single number, or a vector of length nSites.

timeEffectSize

Strength of the seasonality effect. Either a single number, or a vector of length nSites.

minBackgroundRate

Minimum background outcome rate. Either a single number, or a vector of length nSites.

maxBackgroundRate

Maximum background outcome rate. Either a single number, or a vector of length nSites.

rateRatio

The incidence rate ratio.

randomEffectSd

Standard deviation of the log(hazardRatio). Fixed effect if equal to 0.

See Also

simulatePopulations

Examples

settings <- createSccsSimulationSettings(nSites = 1, rateRatio = 2)
populations <- simulatePopulations(settings)

# Fit a SCCS regression for the simulated data site:
cyclopsData <- Cyclops::createCyclopsData(
  y ~ a + x1 + x2 + x3 + x4 + x5 + strata(stratumId) + offset(log(time)),
  data = populations[[1]],
  modelType = "cpr"
)
cyclopsFit <- Cyclops::fitCyclopsModel(cyclopsData)
coef(cyclopsFit)

# (Estimates in this example will vary due to the random simulation)