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Changelog

Source: NEWS.md

rbmi (development version)

New Features

  • pool() gains a rubin_df_method argument. The default "barnard-rubin" uses the Barnard-Rubin small-sample degrees-of-freedom adjustment, while "rubin" uses the original approximation from Rubin (1987).
  • ancova() now supports the analysis of two or more treatment groups. For more than two groups the ref / alt naming scheme is extended with alt2, alt3, etc. based on the factor levels of vars$group; the two-group output is unchanged (trt, lsm_ref, lsm_alt) for backwards compatibility. set_vars() gained a group_contrasts argument allowing users to specify a bespoke set of treatment-group contrasts for ancova(). By default a contrast of each non-reference group versus the reference group is estimated. Custom contrasts must be named (the name becomes the output parameter name) and may be given as pairwise c(minuend, subtrahend) character vectors or as general named numeric weight vectors over the group levels (e.g. c(Placebo = -1, A = 0.5, B = 0.5) for a pooled comparison); contrasts are evaluated in a contrast-coding-agnostic way. The data.frame produced by as.data.frame() / pool() now includes explicit estimate_type, group, group_level_1, group_level_2, contrast_label and visit columns when the analysis was performed with ancova(). The existing parameter column is retained for backwards compatibility. (#520)

rbmi 1.6.1

CRAN release: 2026-07-22

New Features

  • rbmi now uses the lifecycle package
  • Added en-GB spell-check and a corresponding test to the package

Documentation

  • Documented the return value (@return) of all exported functions and marked internal helpers with @keywords internal (#567).
  • Added executable @examples to the exported user-facing functions that were missing them, and marked the internal-only has_class(), validate() and longDataConstructor with @keywords internal (#570).

Bug Fixes

  • The vignette on retrieved dropout methods is now correctly embedded.
  • Fixed numerous spelling errors and standardised nomenclature for missing not at random to MNAR (rather than a mix of NMAR and MNAR)
  • Deprecated nmar.rm argument of longdata$get_data in favour of mnar.rm for nomenclature consistency.
  • Fixed a misleading error message in imputation_list_single() where a failure of the imputation-count-divisible-by-D check incorrectly reported that “multiple ids were detected” (#574)
  • Improved CI/CD scripts to reliably fail GitHub CI/CD in case of failing tests.
  • Fixed error message for mu$visit in simulate_test_data() to refer to visit instead of trt (#578)
  • Fixed a bug where each non-ignorable Stan warning from the Bayesian sampler was reported multiple times instead of once. (#572)
  • Fixed the error message in apply_delta() to correctly refer to data instead of dat (#576)
  • Fixed the broken GitHub badge in README.md (#548)

Miscellaneous

  • Replaced deprecated structure() special name .Dim with dim in unit tests to resolve an R CMD check NOTE (#581)
  • Updated Marcel Wolbers’ e-mail address (#583)

rbmi 1.6.0

CRAN release: 2026-01-23

  • Stan programs are constructed in memory and respect the cache setting
  • Cache default directory location updated to be the local session (e.g. default cache won’t persist across R sessions)
  • Bug fixes to caching hash to better detect when cache is stale
  • Rework of unit tests to have multiple tiers of tests which run under different scenarios
  • Illustrate how to set Stan seed in control_bayes() in the quickstart vignette

rbmi 1.5.2

CRAN release: 2025-10-28

Bug Fixes

  • Disable caching in tests on CRAN and reduce tests run on CRAN to conform to 10-minute limit

rbmi 1.5.1

CRAN release: 2025-10-14

Bug Fixes

  • Modify caching in tests to speed up testing on CRAN.

rbmi 1.5.0

New Features

  • All covariance structures are now also supported for Bayesian multiple imputation: method_bayes() gained additional covariance and prior_cov arguments to allow users to specify the covariance structure and prior for the Bayesian imputation model. Please see the updated statistical specifications vignette for details. (#501, #518)
  • New function mcse() to calculate the Monte Carlo standard error for pooled estimates from (approximate) Bayesian imputation. (#493)

Bug Fixes

  • Fixed cluster used in parallel test and make sure tests clean up Stan files properly. (#523)
  • Small updates and fixes to documentation. (#504, #506, #498)

rbmi 1.4.1

CRAN release: 2025-03-03

Bug Fixes

  • Fixed Stan related bug that caused unit tests to fail on machines compiling with the C23 standard (#481)
  • Fixed bug in unit test that caused false-positive reproducibility errors (#483)

rbmi 1.4.0

CRAN release: 2025-02-07

Breaking Changes

  • Deprecated the burn_in and burn_between arguments in method_bayes() in favour of using the warmup and thin arguments, respectively, in the new control list produced by control_bayes. This is to align with the rstan package. (#477)

New Features

  • Added control_bayes() function to allow expert users to specify additional control arguments for the MCMC computations using rstan. (#477)

Bug Fixes

  • Fixed bug where lsmeans(.weights = "proportional_em") would error if there was only a single categorical variable in the dataset. (#412)
  • Removed native pipes |> and lambda functions \(x) from code base to ensure package is backwards compatible with older versions of R. (#474)

rbmi 1.3.1

CRAN release: 2024-12-11

  • Fixed bug where stale caches of the rstan model were not being correctly cleared (#459)

rbmi 1.3.0

CRAN release: 2024-10-16

Breaking Changes

  • Convert rstan to be a suggested package to simplify the installation process. This means that the Bayesian imputation functionality will not be available by default. To use this feature, you will need to install rstan separately (#441)
  • Deprecated the seed argument to method_bayes() in favour of using the base set.seed() function (#431)

New Features

  • Added vignette on how to implement retrieved dropout models with time-varying intercurrent event (ICE) indicators (#414)
  • Added vignette on how to obtain frequentist and information-anchored inference with conditional mean imputation using rbmi (#406)
  • Added FAQ vignette including a statement on validation (#407 #440)
  • Updates to lsmeans() for better consistency with the emmeans package (#412)
    • Renamed lsmeans(..., weights = "proportional") to lsmeans(..., weights = "counterfactual")to more accurately reflect the weights used in the calculation.
    • Added lsmeans(..., weights = "proportional_em") which provides consistent results with emmeans(..., weights = "proportional")
    • lsmeans(..., weights = "proportional") has been left in the package for backwards compatibility and is an alias for lsmeans(..., weights = "counterfactual") but now gives a message prompting users to use either “proportional_em” or “counterfactual” instead.
  • Added support for parallel processing in the analyse() function (#370)
  • Added documentation clarifying potential false-positive warnings from rstan (#288)
  • Added support for all covariance structures supported by the mmrm package (#437)
  • Updated rbmi citation detail (#423 #425)

Miscellaneous Bug Fixes

  • Stopped warning messages being accidentally suppressed when changing the ICE type in impute() (#408)
  • Fixed equations not rendering properly in the pkgdown website (#433)

rbmi 1.2.6

CRAN release: 2023-11-24

  • Updated unit tests to fix false-positive error on CRAN testing servers

rbmi 1.2.5

CRAN release: 2023-09-20

  • Updated internal Stan code to ensure future compatibility (@andrjohns, #390)
  • Updated package description to include relevant references (#393)
  • Fixed documentation typos (#393)

rbmi 1.2.3

CRAN release: 2022-11-14

  • Minor internal tweaks to ensure compatibility with the packages rbmi depends on

rbmi 1.2.1

CRAN release: 2022-10-25

  • Removed native pipes |> in testing code so package is backwards compatible with older servers
  • Replaced our glmmTMB dependency with the mmrm package. This has resulted in the package being more stable (less model fitting convergence issues) as well as speeding up run times 3-fold.

rbmi 1.1.4

CRAN release: 2022-05-18

  • Updated URLs for references in vignettes
  • Fixed a bug where visit factor levels were re-constructed incorrectly in delta_template()
  • Fixed a bug where the wrong visit was displayed in the error message for when a specific visit doesn’t have any data in draws()
  • Fixed a bug where the wrong input parameter was displayed in an error message in simulate_data()

rbmi 1.1.1 & 1.1.3

CRAN release: 2022-03-08

  • No change in functionality from 1.1.0
  • Various minor tweaks to address CRAN checks messages

rbmi 1.1.0

CRAN release: 2022-03-02

  • Initial public release