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'.">

mmrm: Mixed Models for Repeated Measures (original) (raw)

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

Author:

Daniel Sabanes BoveORCID 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 KriegerORCID 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]