v0.4.0

• Feature: Node-splitting models for assessing inconsistency are now available with consistency = "nodesplit" in nma(). Comparisons to split can be chosen using the nodesplit argument, by default all possibly inconsistent comparisons are chosen using get_nodesplits(). Node-splitting results can be summarised with summary.nma_nodesplit() and plotted with plot.nodesplit_summary().
• Feature: The correlation matrix for generating integration points with add_integration() for ML-NMR models is now adjusted to the underlying Gaussian copula, so that the output correlations of the integration points better match the requested input correlations. A new argument cor_adjust controls this behaviour, with options "spearman", "pearson", or "none". Although these correlations typically have little impact on the results, for strict reproducibility the old behaviour from version 0.3.0 and below is available with cor_adjust = "legacy".
• Feature: For random effects models, the predictive distribution of relative/absolute effects in a new study can now be obtained in relative_effects() and predict.stan_nma() respectively, using the new argument predictive_distribution = TRUE.
• Feature: Added option to calculate SUCRA values when summarising the posterior treatment ranks with posterior_ranks() or posterior_rank_probs(), when argument sucra = TRUE.
• Improvement: Factor order is now respected when trt, study, or trt_class are factors, previously the order of levels was reset into natural sort order.
• Improvement: Update package website to Bootstrap 5 with release of pkgdown 2.0.0
• Fix: Model fitting is now robust to non-default settings of options("contrasts").
• Fix: plot.nma_data() no longer gives a ggplot deprecation warning (PR #6).
• Fix: Bug in predict.stan_nma() with a single covariate when newdata is a data.frame (PR #7).
• Fix: Attempting to call predict.stan_nma() on a regression model with only contrast data and no newdata or baseline specified now throws a descriptive error message.