tern.mmrm provides an interface for mixed model repeated measures (MMRM) within the tern framework to produce commonly used tables (using rtables and graphs. It builds on the R-package mmrm for the actual MMRM calculations.
If you would like to use the tern framework for tabulation and graphs, then this package is ideal for your MMRM fits. However if you use another reporting framework then it will be better to directly use mmrm and perform the tabulation and plots differently.
tern.mmrm is available on CRAN and you can install the latest released version with:
install.packages("tern.mmrm")
or you can install the latest development version directly from GitHub by running the following:
# install.packages("pak")
pak::pak("insightsengineering/tern.mmrm")
You can get started by trying out the example:
library(tern.mmrm)
fit <- fit_mmrm(
vars = list(
response = "FEV1",
covariates = c("RACE", "SEX"),
id = "USUBJID",
arm = "ARMCD",
visit = "AVISIT"
),
data = mmrm_test_data,
cor_struct = "unstructured",
weights_emmeans = "equal",
averages_emmeans = list(
"VIS1+2" = c("VIS1", "VIS2")
)
)
This specifies an MMRM with the FEV1 outcome and the RACE and SEX covariates for subjects identified by USUBJID and treatment arm ARMCD observed over time points identified by AVISIT in the mmrm_test_data data set. An unstructured covariance matrix is assumed. Note that only restricted maximum likelihood (REML) can be used. The least square means assume equal weights for factor combinations, and in addition to the single visit specific results an average across visits VIS1 and VIS2 will be computed.
For a more detailed introduction to all of the features of this package, look at the introduction vignette:
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