Synthesizing Causal Evidence in a Distributed Research Network

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Documentation for package ‘EvidenceSynthesis’ version 0.5.0

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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