Reference

All functions

approximateHierarchicalNormalPosterior()

Approximate Bayesian posterior for hierarchical Normal model

approximateLikelihood()

Approximate a likelihood function

approximateSimplePosterior()

Approximate simple Bayesian posterior

biasCorrectionInference()

Bias Correction with Inference

computeBayesianMetaAnalysis()

Compute a Bayesian random-effects meta-analysis

computeConfidenceInterval()

Compute the point estimate and confidence interval given a likelihood function approximation

computeFixedEffectMetaAnalysis()

Compute a fixed-effect meta-analysis

createSimulationSettings()

Create simulation settings

customFunction()

A custom function to approximate a log likelihood function

detectApproximationType()

Detect the type of likelihood approximation based on the data format

fitBiasDistribution()

Fit Bias Distribution

ncLikelihoods

Example profile likelihoods for negative control outcomes

ooiLikelihoods

Example profile likelihoods for a synthetic outcome of interest

plotBiasCorrectionInference()

Plot bias correction inference

plotBiasDistribution()

Plot bias distributions

plotCovariateBalances()

Plot covariate balances

plotEmpiricalNulls()

Plot empirical null distributions

plotLikelihoodFit()

Plot the likelihood approximation

plotMcmcTrace()

Plot MCMC trace

plotMetaAnalysisForest()

Create a forest plot

plotPerDbMcmcTrace()

Plot MCMC trace for individual databases

plotPerDbPosterior()

Plot posterior density per database

plotPosterior()

Plot posterior density

plotPreparedPs()

Plot the propensity score distribution

preparePsPlot()

Prepare to plot the propensity score distribution

sequentialFitBiasDistribution()

Fit Bias Distribution Sequentially or in Groups

simulatePopulations()

Simulate survival data for multiple databases

skewNormal()

The skew normal function to approximate a log likelihood function

supportsJava8()

Determine if Java virtual machine supports Java