Package: bayesmeta 3.4
bayesmeta: Bayesian Random-Effects Meta-Analysis and Meta-Regression
A collection of functions allowing to derive the posterior distribution of the model parameters in random-effects meta-analysis or meta-regression, and providing functionality to evaluate joint and marginal posterior probability distributions, predictive distributions, shrinkage effects, posterior predictive p-values, etc.; For more details, see also Roever C (2020) <doi:10.18637/jss.v093.i06>, or Roever C and Friede T (2022) <doi:10.1016/j.cmpb.2022.107303>.
Authors:
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bayesmeta/json (API)
# Install 'bayesmeta' in R: |
install.packages('bayesmeta', repos = c('https://christianroever.r-universe.dev', 'https://cloud.r-project.org')) |
- BaetenEtAl2013 - Ankylosing spondylitis example data
- BucherEtAl1997 - Direct and indirect comparison example data
- Cochran1954 - Fly counts example data
- CrinsEtAl2014 - Pediatric liver transplant example data
- GoralczykEtAl2011 - Liver transplant example data
- HinksEtAl2010 - JIA example data
- KarnerEtAl2014 - COPD example data
- NicholasEtAl2019 - Multiple sclerosis disability progression example data
- Peto1980 - Aspirin after myocardial infarction example data
- RobergeEtAl2017 - Aspirin during pregnancy example data
- Rubin1981 - 8-schools example data
- SchmidliEtAl2017 - Historical variance example data
- SidikJonkman2007 - Postoperative complication odds example data
- SnedecorCochran - Artificial insemination of cows example data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:e7eaba2af6. Checks:OK: 5 NOTE: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 13 2024 |
R-4.5-win | NOTE | Oct 13 2024 |
R-4.5-linux | NOTE | Oct 13 2024 |
R-4.4-win | OK | Oct 13 2024 |
R-4.4-mac | OK | Oct 13 2024 |
R-4.3-win | OK | Oct 13 2024 |
R-4.3-mac | OK | Oct 13 2024 |
Exports:bayesmetabmrconvolvedhalfcauchydhalflogisticdhalfnormaldhalftdinvchidlomaxdrayleighehalfcauchyehalflogisticehalfnormalehalfteinvchielomaxerayleighessforestplot.bayesmetaforestplot.bmrforestplot.escalcfunnel.bayesmetakldivnormalmixturepairs.bmrphalfcauchyphalflogisticphalfnormalphalftpinvchiplomaxplot.bayesmetaplot.bmrpppvalueprayleighprint.bayesmetaprint.bmrprint.summary.bmrqhalfcauchyqhalflogisticqhalfnormalqhalftqinvchiqlomaxqrayleighrhalfcauchyrhalflogisticrhalfnormalrhalftRhodesEtAlParametersRhodesEtAlPriorrinvchirlomaxrrayleighsummary.bayesmetasummary.bmrtraceplotTurnerEtAlParametersTurnerEtAlPrioruisdvhalfcauchyvhalflogisticvhalfnormalvhalftvinvchivlomaxvrayleighweightsplot
Dependencies:abindbackportscheckmateforestplotlatticemathjaxrMatrixmetadatmetaformvtnormnlmenumDerivpbapply
Bayesian random-effects meta-analysis using the bayesmeta R package
Rendered fromRoever2020-bayesmeta.pdf.asis
usingR.rsp::asis
on Oct 13 2024.Last update: 2020-12-15
Started: 2020-12-15
An introduction to meta-analysis using the bayesmeta package
Rendered frombayesmeta.Rmd
usingknitr::rmarkdown
on Oct 13 2024.Last update: 2021-08-12
Started: 2015-12-16
Using the bayesmeta R package for Bayesian random-effects meta-regression
Rendered fromRoeverFriede2023-UsingBayesmetaForMetaRegression.pdf.asis
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on Oct 13 2024.Last update: 2023-06-27
Started: 2023-06-27