EvidenceSynthesis0.5.0 package

Synthesizing Causal Evidence in a Distributed Research Network

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 ...

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

EvidenceSynthesis-package

EvidenceSynthesis: Synthesizing Causal Evidence in a Distributed Resea...

fitBiasDistribution

Fit Bias Distribution

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

Routines for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study, without sharing patient-level data. Allows for normal and non-normal approximations of the data-site likelihood of the effect parameter.

  • Maintainer: Martijn Schuemie
  • License: Apache License 2.0
  • Last published: 2023-05-08