c(
person("Daniel", "Sabanes Bove", , "daniel.sabanes_bove@roche.com", role = c("aut", "cre")),
person("Julia", "Dedic", , "julia.dedic@roche.com", role = "aut"),
person("Doug", "Kelkhoff", , "kelkhoff.douglas@gene.com", role = "aut"),
person("Kevin", "Kunzmann", , "kevin.kunzmann@boehringer-ingelheim.com", role = "aut"),
person("Brian Matthew", "Lang", , "brian.lang@msd.com", role = "aut"),
person("Liming", "Li", , "liming.li@roche.com", role = "aut"),
person("Ya", "Wang", , "ya.wang10@gilead.com", role = "aut"),
person("Craig", "Gower-Page", , "craig.gower-page@roche.com", role = "ctb"),
person("Boehringer Ingelheim Ltd.", role = c("cph", "fnd")),
person("Gilead Sciences, Inc.", role = c("cph", "fnd")),
person("F. Hoffmann-La Roche AG", role = c("cph", "fnd")),
person("Merck Sharp & Dohme, Inc.", role = c("cph", "fnd"))
)
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<2349::AID-SIM667>3.0.CO;2-E>
for a tutorial and Mallinckrodt, Lane and Schnell (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
adjusted degrees of freedom, and extract least square means estimates
by using 'emmeans'.
checkmate (>= 2.0), lifecycle, methods, nlme, numDeriv,
parallel, Rdpack, stats, stringr, TMB (>= 1.9.1)
emmeans (>= 1.6), estimability, knitr, rmarkdown, testthat
(>= 3.0.0), xml2
'catch-routine-registration.R' 'component.R' 'data.R'
'emmeans.R' 'fit.R' 'mmrm-methods.R' 'mmrm-package.R' 'utils.R'
'satterthwaite.R' 'tmb-methods.R' 'tmb.R'
Daniel Sabanes Bove [aut, cre],
Julia Dedic [aut],
Doug Kelkhoff [aut],
Kevin Kunzmann [aut],
Brian Matthew Lang [aut],
Liming Li [aut],
Ya Wang [aut],
Craig Gower-Page [ctb],
Boehringer Ingelheim Ltd. [cph, fnd],
Gilead Sciences, Inc. [cph, fnd],
F. Hoffmann-La Roche AG [cph, fnd],
Merck Sharp & Dohme, Inc. [cph, fnd]