Package: RBesT 1.7-4

Sebastian Weber

RBesT: R Bayesian Evidence Synthesis Tools

Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases). Please refer to Weber et al. (2021) <doi:10.18637/jss.v100.i19> for details on applying this package while Neuenschwander et al. (2010) <doi:10.1177/1740774509356002> and Schmidli et al. (2014) <doi:10.1111/biom.12242> explain details on the methodology.

Authors:Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Beat Neuenschwander [ctb], Heinz Schmidli [ctb], Baldur Magnusson [ctb], Yue Li [ctb], Satrajit Roychoudhury [ctb], Trustees of Columbia University [cph]

RBesT_1.7-4.tar.gz
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RBesT.pdf |RBesT.html
RBesT/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/novartis/rbest/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

bayesianclinicalhistorical-datameta-analysis

7.39 score 20 stars 4 packages 103 scripts 859 downloads 1 mentions 44 exports 64 dependencies

Last updated 8 hours agofrom:bb349616ab. Checks:OK: 2 NOTE: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-win-x86_64NOTENov 21 2024
R-4.5-linux-x86_64OKNov 21 2024
R-4.4-win-x86_64NOTENov 21 2024
R-4.4-mac-x86_64NOTENov 21 2024
R-4.4-mac-aarch64NOTENov 21 2024
R-4.3-win-x86_64NOTENov 21 2024
R-4.3-mac-x86_64NOTENov 21 2024
R-4.3-mac-aarch64NOTENov 21 2024

Exports:automixfitBinaryExactCIdecision1Sdecision1S_boundarydecision2Sdecision2S_boundarydmixdmixdiffessforest_plotgMAPinv_logitlikelihoodlikelihood<-logitmixbetamixcombinemixfitmixgammamixmvnormmixnormmixstanvarmn2betamn2gammamn2normms2betams2gammaoc1Soc1Sdecisionoc2Soc2Sdecisionpmixpmixdiffpos1Spos2Spostmixpreddistqmixqmixdiffrmixrmixdiffrobustifysigmasigma<-

Dependencies:abindassertthatbackportsbayesplotBHcallrcheckmateclicolorspacedescdistributionaldplyrfansifarverFormulagenericsggplot2ggridgesgluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnlmenumDerivpillarpkgbuildpkgconfigplyrposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstanrstantoolsscalesStanHeadersstringistringrtensorAtibbletidyselectutf8vctrsviridisLitewithr

Getting started with RBesT (binary)

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Nov 21 2024.

Last update: 2024-11-21
Started: 2023-02-07

Readme and manuals

Help Manual

Help pageTopics
R Bayesian Evidence Synthesis ToolsRBesT-package RBesT
Ankylosing Spondylitis.AS
Automatic Fitting of Mixtures of Conjugate Distributions to a Sampleautomixfit
Exact Confidence interval for Binary ProportionBinaryExactCI
Ulcerative Colitis.colitis
Crohn's disease.crohn
Decision Function for 1 Sample Designsdecision1S oc1Sdecision
Decision Boundary for 1 Sample Designsdecision1S_boundary decision1S_boundary.betaMix decision1S_boundary.gammaMix decision1S_boundary.normMix
Decision Function for 2 Sample Designsdecision2S oc2Sdecision
Decision Boundary for 2 Sample Designsdecision2S_boundary decision2S_boundary.betaMix decision2S_boundary.gammaMix decision2S_boundary.normMix
Effective Sample Size for a Conjugate Prioress ess.betaMix ess.gammaMix ess.normMix
Forest Plotforest_plot
Meta-Analytic-Predictive Analysis for Generalized Linear Modelsas.matrix.gMAP coef.gMAP fitted.gMAP gMAP print.gMAP summary.gMAP
Read and Set Likelihood to the Corresponding Conjugate Priorlikelihood likelihood<-
Logit (log-odds) and inverse-logit function.inv_logit lodds logit
Mixture Distributionsdmix mix pmix qmix rmix [[.mix
Beta Mixture Densitymixbeta mn2beta ms2beta print.betaBinomialMix print.betaMix summary.betaBinomialMix summary.betaMix
Combine Mixture Distributionsmixcombine
Difference of mixture distributionsdmixdiff mixdiff pmixdiff qmixdiff rmixdiff
Fit of Mixture Densities to Samplesmixfit mixfit.array mixfit.default mixfit.gMAP mixfit.gMAPpred
The Gamma Mixture Distributionmixgamma mn2gamma ms2gamma print.gammaExpMix print.gammaMix print.gammaPoissonMix summary.gammaMix summary.gammaPoissonMix
Multivariate Normal Mixture Densitymixmvnorm print.mvnormMix sigma.mvnormMix summary.mvnormMix
Normal Mixture Densitymixnorm mn2norm print.normMix sigma sigma.normMix sigma<- summary.normMix
Plot mixture distributionsmixplot plot.mix plot.mvnormMix
Mixture distributions as 'brms' priorsmixstanvar
Operating Characteristics for 1 Sample Designoc1S oc1S.betaMix oc1S.gammaMix oc1S.normMix
Operating Characteristics for 2 Sample Designoc2S oc2S.betaMix oc2S.gammaMix oc2S.normMix
Diagnostic plots for EM fitsplot.EM
Diagnostic plots for gMAP analysesplot.gMAP
Probability of Success for a 1 Sample Designpos1S pos1S.betaMix pos1S.gammaMix pos1S.normMix
Probability of Success for 2 Sample Designpos2S pos2S.betaMix pos2S.gammaMix pos2S.normMix
Conjugate Posterior Analysispostmix postmix.betaMix postmix.gammaMix postmix.normMix
Predictive Distributions for Mixture Distributionspreddist preddist.betaMix preddist.gammaMix preddist.mvnormMix preddist.normMix
Predictions from gMAP analysesas.matrix.gMAPpred predict.gMAP print.gMAPpred summary.gMAPpred
Robustify Mixture Priorsrobustify robustify.betaMix robustify.gammaMix robustify.normMix
Transplant.transplant