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.2022mmrm_test_data as sample data.tern.