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mmrm's Introduction

MMRM

R package to fit Mixed Model for Repeated Measures as is commonly used to analyze clinical trial data. This package uses nlme::gls to fit the model, and provides support for Kenward-Rogers degrees of freedom calculation.

This package is currently in beta version -- more testing and examples to come!

Installation

if(!requireNamespace("remotes")) install.packages("remotes")
remotes::install_github("alto-neuroscience/MMRM")

Example

library(MMRM)


# fit an MMRM
my_mmrm = MMRM::mmrm(outcome ~ baseline + group + time + baseline:time + group:time,
                     time = "time",
                     subjects = "subjects",
                     data = my_data)
                     
# fit MMRM using k-fold cross validation (steps below work the same)
my_mmrm = MMRM::mmrm_cv(outcome ~ baseline + group + time + baseline:time + group:time,
                     time = "time",
                     subjects = "subjects",
                     data = my_data,
                     k = 10)

# get estimated marginal means
mmrm_emm = MMRM::mmrm_emmeans(my_mmrm,
                              pairwise ~ group | time,
                              mode = "kenward")

# calculate effect size
mmrm_eff = MMRM::mmrm_eff_size(my_mmrm, mmrm_emm)

mmrm's People

Stargazers

Alberto Jaramillo Jiménez avatar

Watchers

 avatar Patrick Staples avatar Chao avatar Gary Kane avatar

mmrm's Issues

Connecting about mmrm package landscape

Hi @gkane26, I wanted to reach out to connect you with another project focused on improving methods for MMRM in R over at https://github.com/openpharma/mmrm

If you're aware of that work and felt it was missing something, we'd be very interested to learn about what gaps you felt were prohibitive.

Or, if this looks like it could be a good fit for you, we would also love to join forces to build a more robust MMRM solution.

Let us know what you think - either way we'd love to hear from you. We're always keen to connect with knowledgeable domain experts.


Just for transparency, tagging a few other members of that project, @danielinteractive @clarkliming

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