Create an object specifying a simulation for the Self-Controlled Case Series (SCCS).
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
)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.
Value
An object of type simulationSccsSettings, to be used in the simulatePopulations() function.
See also
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)
#> a x1 x2 x3 x4 x5
#> 0.50702050 -0.89521673 -0.10599550 -0.69481827 0.32917307 -0.04000263
# (Estimates in this example will vary due to the random simulation)