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Adapt to release 0.3 of the mmrm
package.
...
to mmrm::mmrm
when calling fit_mmrm
. In particular, the method
argument allows to choose Kenward-Roger adjustment of degrees of freedom and coefficients covariance matrix.optimizer
argument when calling fit_mmrm
.parallelly
is now used internally to handle the determination of available cores.mmrm
package instead of lme4
and lmerTest
. This greatly increases convergence and speed. Different covariance structures and optimizers are now available compared to before.g_covariance()
to visualize a covariance matrix, which can be helpful for choosing or visualizing the covariance structure in the MMRM.averages_emmeans
to fit_mmrm()
which allows estimation of least square means for averages of visits.accept_singular
to fit_mmrm()
which allows estimation of rank-deficient models (like lm()
and gls()
) by omitting the columns of singular coefficients from the design matrix.show_lines
and xlab
to g_mmrm_lsmeans()
which allow the addition of lines connecting the estimates, as well as a custom x-axis label.table_stats
, table_formats
, table_labels
, table_font_size
, and table_rel_height
to g_mmrm_lsmeans()
which allow the addition of and configure the appearance of an LS means estimates statistics table below the LS means estimates plot.constant_baseline
and n_baseline
to g_mmrm_lsmeans()
which allow plotting of a constant baseline value and specifying the corresponding number of patients (visible in the optional table) for the LS means plots.purrr
, tibble
, scda
and scda.2022
mmrm_test_data
as sample data.tern
.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.