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brms.mmrmhttps://openpharma.github.io/brms.mmrm/

CRANstatuscheckcoverlint

Themixedmodel for repeated measures (MMRM) is a popular model forlongitudinal clinical trial data with continuous endpoints, andbrms is powerfuland versatile package for fitting Bayesian regression models. Thebrms.mmrm R package leveragesbrms to runMMRMs,and it supports a simplified interface to reduce difficulty and alignwith best practices for the life sciences.

Installation

TypeSourceCommand
ReleaseCRANinstall.packages("brms.mmrm")
DevelopmentGitHubremotes::install_github("openpharma/brms.mmrm")
Developmentopenpharmainstall.packages("brms.mmrm", repos = "https://openpharma.r-universe.dev")

Documentation

The documentation website athttps://openpharma.github.io/brms.mmrm/ has a completefunction reference and tutorial vignettes.

Validation

To ensure the correctness of the model and its implementation, thispackage has been validated using simulation-based calibration andcomparisons against the frequentistmmrmpackage on two example datasets. The analyses and results are describedin the package vignettes linked below:

Notably,FEV1andBCVAare the same datasets thatmmrmuses to compare itself against SAS inthisvignette. For additional validation in your functional area ordomain of expertise, you may choose to run similar analyses on your owndatasets to comparebrms.mmrm againstmmrmand/or SAS.

Help

Please report questions and problems asGitHub discussionsandGitHub issues,respectively.

Thanks

Thanks to theopenstatsware andR Consortium for providingprofessional networks to recruit skilled statisticians anddevelopers.

Code of conduct

Please note that the brms.mmrm project is released with aContributorCode of Conduct. By contributing to this project, you agree to abideby its terms.

Citation

To cite package 'brms.mmrm' in publications use:  Landau WM, Kunzmann K, Sidi Y, Stock C (????). _brms.mmrm: Bayesian  MMRMs using 'brms'_. R package version 1.1.0.9002,  <https://github.com/openpharma/brms.mmrm>.A BibTeX entry for LaTeX users is  @Manual{,    title = {brms.mmrm: Bayesian MMRMs using 'brms'},    author = {William Michael Landau and Kevin Kunzmann and Yoni Sidi and Christian Stock},    note = {R package version 1.1.0.9002},    url = {https://github.com/openpharma/brms.mmrm},  }

References


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