describe_draws() extracts structured metadata from rbmi draws objects, including method type, formula, sample count, and (for Bayesian methods) MCMC convergence diagnostics (ESS, Rhat).
describe_imputation() extracts imputation metadata including method, number of imputations (M), reference arm mappings, and a missingness breakdown by visit and treatment arm.
pool_to_ard() gains an analysis_obj parameter that enriches the ARD with MI diagnostic statistics (FMI, lambda, RIV, Barnard-Rubin adjusted df, relative efficiency) when the pooling method is Rubin’s rules.
Improvements
efficacy_table() gains font_family, font_size, and row_padding parameters for publication-ready table styling.
plot_forest() gains font_family and panel_widths parameters for customizable typography and panel layout.
plot_forest() left panel now uses left-aligned text (hjust=0) for consistent positioning regardless of label length.
Non-Rubin pooling methods now emit an informative cli::cli_inform() message when MI diagnostics are not applicable, rather than returning NA rows.
rbmiUtils 0.2.1
New Features
End-to-end pipeline vignette “From rbmi Analysis to Regulatory Tables” with continuous and binary analysis walkthroughs.
README enhanced with rendered efficacy table and forest plot visual teasers.
Inline cross-references to rbmi and beeca documentation in all vignettes.
Improvements
validate_data() now uses cli-formatted error messages with clearer guidance for malformed interaction terms, empty data, and type mismatches.
prepare_data_ice() now errors immediately when vars$strategy is NULL instead of silently using a default column name.
prepare_data_ice() warns when visit column is character with guidance to convert to factor for correct ordering.
validate_data() batches all type coercion warnings into a single message and warns on all-NA covariate columns.
Data preparation functions handle edge cases (single subject, single visit, all-NA outcome, all-complete data) gracefully.
rbmiUtils 0.2.0
Breaking Changes
tidy_pool_obj() now uses regex-based parameter parsing instead of splitting on _. Output columns (parameter_type, lsm_type, visit) now contain the full visit name rather than truncated fragments.
New Features
efficacy_table() creates regulatory-style gt summary tables from pool objects.
plot_forest() creates publication-quality three-panel forest plots from pool objects.
pool_to_ard() converts pool objects to pharmaverse ARD format via the cards package.
