simulateMetaAnalysisWithNegativeControls: Simulate survival data across a federated data network, with...

In EvidenceSynthesis: Synthesizing Causal Evidence in a Distributed Research Network

Simulate survival data across a federated data network, with negative control outcomes as well.

Description

A function to simulate patient-level survival data for a hypothetical exposure, with simulated bias and data-source-specific random effects. Patient-level data for negative control outcomes are simulated as well to reflect systematic error.

Usage

simulateMetaAnalysisWithNegativeControls(
  meanExposureEffect = log(2),
  meanBias = 0.5,
  biasStd = 0.2,
  meanSiteEffect = 0,
  siteEffectStd = 0.1,
  mNegativeControls = 10,
  nSites = 10,
  sitePop = 2000,
  seed = 42,
  ...
)

Arguments

meanExposureEffect	Average exposure effect; has to be on the log-scale
meanBias	Average bias for the bias distribution
biasStd	Standard deviation for the bias distribution
meanSiteEffect	Average of the data-source-specific effects (typically should be zero)
siteEffectStd	Standard deviation for data-source-specific effects
mNegativeControls	Number of negative control outcomes
nSites	Number of data sources
sitePop	Population size per data source
seed	Random seed
...	Arguments that will be passed to other functions

See Also

computeHierarchicalMetaAnalysis

EvidenceSynthesis documentation built on Aug. 26, 2025, 9:08 a.m.