mmrm: Mixed Models for Repeated Measures

Mixed models for repeated measures (MMRM) are a popular choice for analyzing longitudinal continuous outcomes in randomized clinical trials and beyond; see Cnaan, Laird and Slasor (1997) <doi:10.1002/(SICI)1097-0258(19971030)16:20%3C2349::AID-SIM667%3E3.0.CO;2-E> for a tutorial and Mallinckrodt, Lane, Schnell, Peng and Mancuso (2008) <doi:10.1177/009286150804200402> for a review. This package implements MMRM based on the marginal linear model without random effects using Template Model Builder ('TMB') which enables fast and robust model fitting. Users can specify a variety of covariance matrices, weight observations, fit models with restricted or standard maximum likelihood inference, perform hypothesis testing with Satterthwaite or Kenward-Roger adjustment, and extract least square means estimates by using 'emmeans'.

Version: 0.3.15
Depends: R (≥ 4.1)
Imports: checkmate (≥ 2.0), generics, lifecycle, Matrix, methods, nlme, parallel, Rcpp, Rdpack, stats, stringr, tibble, TMB (≥ 1.9.1), utils
LinkingTo: Rcpp, RcppEigen, testthat, TMB (≥ 1.9.1)
Suggests: broom.helpers, car (≥ 3.1.2), cli, clubSandwich, clusterGeneration, dplyr, emmeans (≥ 1.6), estimability, ggplot2, glmmTMB, hardhat, knitr, lme4, MASS, microbenchmark, mockery, parallelly (≥ 1.32.0), parsnip (≥ 1.1.0), purrr, rmarkdown, sasr, scales, testthat (≥ 3.0.0), tidymodels, withr, xml2
Published: 2025-06-10
DOI: 10.32614/CRAN.package.mmrm
Author: Daniel Sabanes Bove ORCID iD [aut, cre], Liming Li ORCID iD [aut], Julia Dedic [aut], Doug Kelkhoff [aut], Kevin Kunzmann [aut], Brian Matthew Lang [aut], Christian Stock [aut], Ya Wang [aut], Craig Gower-Page [ctb], Dan James [aut], Jonathan Sidi [aut], Daniel Leibovitz [aut], Daniel D. Sjoberg ORCID iD [aut], Nikolas Ivan Krieger ORCID iD [aut], Lukas A. Widmer ORCID iD [ctb], Boehringer Ingelheim Ltd. [cph, fnd], Gilead Sciences, Inc. [cph, fnd], F. Hoffmann-La Roche AG [cph, fnd], Merck Sharp & Dohme, Inc. [cph, fnd], AstraZeneca plc [cph, fnd], inferential.biostatistics GmbH [cph, fnd]
Maintainer: Daniel Sabanes Bove <daniel.sabanes_bove at rconis.com>
BugReports: https://github.com/openpharma/mmrm/issues
License: Apache License 2.0
URL: https://openpharma.github.io/mmrm/
NeedsCompilation: yes
Language: en-US
Materials: NEWS
In views: ClinicalTrials, MixedModels
CRAN checks: mmrm results

Documentation:

Reference manual: mmrm.html , mmrm.pdf
Vignettes: Model Fitting Algorithm (source, R code)
Between-Within (source, R code)
Coefficients Covariance Matrix Adjustment (source, R code)
Covariance Structures (source, R code)
Details of Weighted Least Square Empirical Covariance (source)
Details of Hypothesis Testing (source, R code)
Package Introduction (source, R code)
Kenward-Roger (source, R code)
Mixed Models for Repeated Measures (source, R code)
Comparison with other software (source, R code)
Package Structure (source)
Prediction and Simulation (source, R code)
Satterthwaite (source, R code)

Downloads:

Package source: mmrm_0.3.15.tar.gz
Windows binaries: r-devel: mmrm_0.3.15.zip, r-release: mmrm_0.3.15.zip, r-oldrel: mmrm_0.3.15.zip
macOS binaries: r-release (arm64): mmrm_0.3.15.tgz, r-oldrel (arm64): mmrm_0.3.15.tgz, r-release (x86_64): mmrm_0.3.15.tgz, r-oldrel (x86_64): mmrm_0.3.15.tgz
Old sources: mmrm archive

Reverse dependencies:

Reverse imports: junco, rbmi, tern.mmrm
Reverse suggests: brms.mmrm, broom.helpers, DoseFinding, insight, parameters

Linking:

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