Package: brms.mmrm 1.1.1
brms.mmrm: Bayesian MMRMs using 'brms'
The mixed model for repeated measures (MMRM) is a popular model for longitudinal clinical trial data with continuous endpoints, and 'brms' is a powerful and versatile package for fitting Bayesian regression models. The 'brms.mmrm' R package leverages 'brms' to run MMRMs, and it supports a simplified interfaced to reduce difficulty and align with the best practices of the life sciences. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>, Mallinckrodt (2008) <doi:10.1177/009286150804200402>.
Authors:
brms.mmrm_1.1.1.tar.gz
brms.mmrm_1.1.1.tar.gz(r-4.5-noble)brms.mmrm_1.1.1.tar.gz(r-4.4-noble)
brms.mmrm_1.1.1.tgz(r-4.4-emscripten)brms.mmrm_1.1.1.tgz(r-4.3-emscripten)
brms.mmrm.pdf |brms.mmrm.html✨
brms.mmrm/json (API)
NEWS
# Install 'brms.mmrm' in R: |
install.packages('brms.mmrm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/openpharma/brms.mmrm/issues
Last updated 2 days agofrom:6b8e69e078. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 03 2024 |
R-4.5-linux | OK | Oct 03 2024 |
Exports:brm_archetype_average_cellsbrm_archetype_average_effectsbrm_archetype_cellsbrm_archetype_effectsbrm_archetype_successive_cellsbrm_archetype_successive_effectsbrm_databrm_data_changebrm_data_chronologizebrm_formulabrm_formula_sigmabrm_marginal_databrm_marginal_drawsbrm_marginal_draws_averagebrm_marginal_gridbrm_marginal_probabilitiesbrm_marginal_summariesbrm_modelbrm_plot_comparebrm_plot_drawsbrm_prior_archetypebrm_prior_labelbrm_prior_simplebrm_prior_templatebrm_recenter_nuisancebrm_simulatebrm_simulate_categoricalbrm_simulate_continuousbrm_simulate_outlinebrm_simulate_priorbrm_simulate_simplebrm_transform_marginal
Dependencies:abindarrayhelpersbackportsbayesplotBHbinombridgesamplingbrmsBrobdingnagcallrcheckmateclicodacodetoolscolorspacecpp11descdigestdistributionaldplyrfansifarverfuturefuture.applygenericsggdistggplot2ggridgesglobalsgluegridExtragtablegtoolsinlineisobandlabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnleqslvnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrquadprogQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstanrstantoolsscalesStanHeadersstringistringrsvUnittensorAtibbletidybayestidyrtidyselecttrialrutf8vctrsviridisLitewithrzoo
BCVA data comparison between Bayesian and frequentist MMRMs
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usingknitr::rmarkdown
on Oct 03 2024.Last update: 2024-07-30
Started: 2024-02-16
FEV1 data comparison between Bayesian and frequentist MMRMs
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usingknitr::rmarkdown
on Oct 03 2024.Last update: 2024-07-30
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Inference
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Informative prior archetypes
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usingknitr::rmarkdown
on Oct 03 2024.Last update: 2024-10-03
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Model
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usingknitr::rmarkdown
on Oct 03 2024.Last update: 2024-10-03
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Simulation
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Simulation-based calibration checking
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usingknitr::rmarkdown
on Oct 03 2024.Last update: 2024-06-05
Started: 2024-02-16
Subgroup analysis
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on Oct 03 2024.Last update: 2024-07-30
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Usage
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usingknitr::rmarkdown
on Oct 03 2024.Last update: 2024-10-03
Started: 2023-08-18