Package: EvidenceSynthesis 0.5.0

Martijn Schuemie

EvidenceSynthesis: Synthesizing Causal Evidence in a Distributed Research Network

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.

Authors:Martijn Schuemie [aut, cre], Marc A. Suchard [aut], Fan Bu [aut], Observational Health Data Science and Informatics [cph]

EvidenceSynthesis_0.5.0.tar.gz
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EvidenceSynthesis.pdf |EvidenceSynthesis.html✨
EvidenceSynthesis/json (API)
NEWS

# Install 'EvidenceSynthesis' in R:
install.packages('EvidenceSynthesis', repos = c('https://ohdsi.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ohdsi/evidencesynthesis/issues

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT
Datasets:
  • ncLikelihoods - Example profile likelihoods for negative control outcomes
  • ooiLikelihoods - Example profile likelihoods for a synthetic outcome of interest

On CRAN:

hades

5.87 score 8 stars 31 scripts 428 downloads 27 exports 82 dependencies

Last updated 2 months agofrom:a4a06fca3b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-winOKNov 03 2024
R-4.5-linuxOKNov 03 2024
R-4.4-winOKNov 03 2024
R-4.4-macOKNov 03 2024
R-4.3-winOKNov 03 2024
R-4.3-macOKNov 03 2024

Exports:approximateHierarchicalNormalPosteriorapproximateLikelihoodapproximateSimplePosteriorbiasCorrectionInferencecomputeBayesianMetaAnalysiscomputeConfidenceIntervalcomputeFixedEffectMetaAnalysiscreateSimulationSettingscustomFunctiondetectApproximationTypefitBiasDistributionplotBiasCorrectionInferenceplotBiasDistributionplotCovariateBalancesplotEmpiricalNullsplotLikelihoodFitplotMcmcTraceplotMetaAnalysisForestplotPerDbMcmcTraceplotPerDbPosteriorplotPosteriorplotPreparedPspreparePsPlotsequentialFitBiasDistributionsimulatePopulationsskewNormalsupportsJava8

Dependencies:AndromedaBeastJarbitbit64blobbootcachemclicliprcodacolorspaceCompQuadFormcpp11crayonCyclopsDBIdbplyrdistributionaldplyrEmpiricalCalibrationfansifarverfastmapgenericsggdistggplot2gluegridExtragtableHDIntervalhmsisobandlabelinglatticelifecyclelme4magrittrMASSmathjaxrMatrixmemoisemetametadatmetaformgcvminqamunsellnlmenloptrnumDerivpbapplypillarpkgconfigplogrprettyunitsprogresspurrrquadprogR6RColorBrewerRcppRcppEigenRcppParallelreadrrJavarlangRSQLitescalesstringistringrsurvivaltibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithrxml2zip

Bayesian adaptive bias correction using profile likelihoods

Fan Bu

Rendered fromBayesianBiasCorrection.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2023-04-27
Started: 2023-04-22

Code used in the video vignette

Martijn Schuemie

Rendered fromVideoVignette.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2023-04-27
Started: 2023-04-05

Effect estimate synthesis using non-normal likelihood approximations

Martijn J. Schuemie

Rendered fromNonNormalEffectSynthesis.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2023-04-27
Started: 2020-10-29

Readme and manuals

Help Manual

Help pageTopics
Approximate Bayesian posterior for hierarchical Normal modelapproximateHierarchicalNormalPosterior
Approximate a likelihood functionapproximateLikelihood
Approximate simple Bayesian posteriorapproximateSimplePosterior
Bias Correction with InferencebiasCorrectionInference
Compute a Bayesian random-effects meta-analysiscomputeBayesianMetaAnalysis
Compute the point estimate and confidence interval given a likelihood function approximationcomputeConfidenceInterval
Compute a fixed-effect meta-analysiscomputeFixedEffectMetaAnalysis
Create simulation settingscreateSimulationSettings
A custom function to approximate a log likelihood functioncustomFunction
Detect the type of likelihood approximation based on the data formatdetectApproximationType
Fit Bias DistributionfitBiasDistribution
Example profile likelihoods for negative control outcomesncLikelihoods
Example profile likelihoods for a synthetic outcome of interestooiLikelihoods
Plot bias correction inferenceplotBiasCorrectionInference
Plot bias distributionsplotBiasDistribution
Plot covariate balancesplotCovariateBalances
Plot empirical null distributionsplotEmpiricalNulls
Plot the likelihood approximationplotLikelihoodFit
Plot MCMC traceplotMcmcTrace
Create a forest plotplotMetaAnalysisForest
Plot MCMC trace for individual databasesplotPerDbMcmcTrace
Plot posterior density per databaseplotPerDbPosterior
Plot posterior densityplotPosterior
Plot the propensity score distributionplotPreparedPs
Prepare to plot the propensity score distributionpreparePsPlot
Fit Bias Distribution Sequentially or in GroupssequentialFitBiasDistribution
Simulate survival data for multiple databasessimulatePopulations
The skew normal function to approximate a log likelihood functionskewNormal
Determine if Java virtual machine supports JavasupportsJava8