Changelog

Source: NEWS.md

bayestestR 0.16.0

CRAN release: 2025-05-20

Changes

• Revised code-base to address changes in latest insight update. Dealing with larger models (many parameters, many posterior samples) from packages brms and rstanarm is more efficient now. Furthermore, the options for the effects argument have a new behavior. "all" only returns fixed effects and random effects variance components, but no longer the group level estimates. Use effects = "full" to return all parameters. This change is mainly to be more flexible and gain more efficiency for models with many parameters and / or many posterior draws.

bayestestR 0.15.3

CRAN release: 2025-04-28

Changes

• effective_sample(), and functions that call effective_sample() (like describe_posterior() with the respective test option) now also return the tail ESS.

Bug fixes

• describe_posterior() now returns a columns with response levels for marginaleffects objects applied to categorical or multinomial Stan models.

• describe_posterior() now returns a columns with response variables for marginaleffects objects applied to multivariate response Stan models.

• Fixed issue in map_estimate() and point_estimate(centrality = "MAP") for vectors with only one unique value.

bayestestR 0.15.2

CRAN release: 2025-02-07

Changes

• describe_posterior() no longer re-samples a model when computing indices.

• describe_posterior() calls tests only when needed. Before, there was a minimal overhead by calling tests that were not requested.

Bug fixes

• Fixed failing test for Mac OS.

bayestestR 0.15.1

CRAN release: 2025-01-17

Changes

• Several minor changes to deal with recent changes in other packages.

Bug fixes

• Fix to emmeans / marginaleffects / data.frame(<rvar>) methods when using multiple credible levels (#688).

bayestestR 0.15.0

CRAN release: 2024-10-17

Changes

• Support for posterior::rvar-type column in data frames. For example, a data frame df with an rvar column ".pred" can now be called directly via p_direction(df, rvar_col = ".pred").

• Added support for marginaleffects

• The ROPE or threshold ranges in rope(), describe_posterior(), p_significance() and equivalence_test() can now be specified as a list. This allows for different ranges for different parameters.

• Results from objects generated by emmeans (emmGrid/emm_list) now return results with appended grid-data.

• Usability improvements for p_direction():

  • Results from p_direction() can directly be used in pd_to_p().

  • p_direction() gets an as_p argument, to directly convert pd-values into frequentist p-values.

  • p_direction() gets a remove_na argument, which defaults to TRUE, to remove NA values from the input before calculating the pd-values.

  • Besides the existing as.numeric() method, p_direction() now also has an as.vector() method.

• p_significance() now accepts non-symmetric ranges for the threshold argument.

• p_to_pd() now also works with data frames returned by p_direction(). If a data frame contains a pd, p_direction or PD column name, this is assumed to be the pd-values, which are then converted to p-values.

• p_to_pd() for data frame inputs gets a as.numeric() and as.vector() method.

Bug fixes

• Fixed warning in CRAN check results.

bayestestR 0.14.0

CRAN release: 2024-07-24

Breaking Changes

• Arguments named group, at, group_by and split_by will be deprecated in future releases of easystats packages. Please use by instead. This affects following functions in bayestestR: estimate_density().

Changes

• bayesian_as_frequentist() now supports more model families from Bayesian models that can be successfully converted to their frequentists counterparts.

• bayesfactor_models() now throws an informative error when Bayes factors for comparisons could not be calculated.

Bug fixes

• Fixed issue in bayesian_as_frequentist() for brms models with 0 + Intercept specification in the model formula.

bayestestR 0.13.2

CRAN release: 2024-02-12

Breaking Changes

• pd_to_p() now returns 1 and a warning for values smaller than 0.5.

• map_estimate(), p_direction(), p_map(), and p_significance() now return a data-frame when the input is a numeric vector. (making the output consistently a data frame for all inputs.)

• Argument posteriors was renamed into posterior. Before, there were a mix of both spellings, now it is consistently posterior.

Changes

• Retrieving models from the environment was improved.

Bug fixes

• Fixed issues in various format() methods, which did not work properly for some few functions (like p_direction()).

• Fixed issue in estimate_density() for double vectors that also had other class attributes.

• Fixed several minor issues and tests.

bayestestR 0.13.1

CRAN release: 2023-04-07

Changes

• Improved speed performance when functions are called using do.call().

• Improved speed performance to bayesfactor_models() for brmsfit objects that already included a marglik element in the model object.

New functionality

• as.logical() for bayesfactor_restricted() results, extracts the boolean vector(s) the mark which draws are part of the order restriction.

Bug fixes

• p_map() gains a new null argument to specify any non-0 nulls.

• Fixed non-working examples for ci(method = "SI").

• Fixed wrong calculation of rope range for model objects in describe_posterior().

• Some smaller bug fixes.

bayestestR 0.13.0

CRAN release: 2022-09-18

Breaking

• The minimum needed R version has been bumped to 3.6.

• contr.equalprior(contrasts = FALSE) (previously contr.orthonorm) no longer returns an identity matrix, but a shifted diag(n) - 1/n, for consistency.

New functionality

• p_to_bf(), to convert p-values into Bayes factors. For more accurate approximate Bayes factors, use bic_to_bf().
• bayestestR now supports objects of class rvar from package posterior.
• contr.equalprior (previously contr.orthonorm) gains two new functions: contr.equalprior_pairs and contr.equalprior_deviations to aide in setting more intuitive priors.

Changes

• has been renamed contr.equalprior to be more explicit about its function.
• p_direction() now accepts objects of class parameters_model() (from parameters::model_parameters()), to compute probability of direction for parameters of frequentist models.

bayestestR 0.12.1

CRAN release: 2022-05-02

Breaking

• Bayesfactor_models() for frequentist models now relies on the updated insight::get_loglikelihood(). This might change some results for REML based models. See documentation.

• estimate_density() argument group_by is renamed at.

• All distribution_*(random = FALSE) functions now rely on ppoints(), which will result in slightly different results, especially with small ns.

• Uncertainty estimation now defaults to "eti" (formerly was "hdi").

Changes

• bayestestR functions now support draws objects from package posterior.

• rope_range() now handles log(normal)-families and models with log-transformed outcomes.

• New function spi(), to compute shortest probability intervals. Furthermore, the "spi" option was added as new method to compute uncertainty intervals.

Bug fixes

• bci() for some objects incorrectly returned the equal-tailed intervals.

bayestestR 0.11.5

CRAN release: 2021-10-30

• Fixes failing tests in CRAN checks.

bayestestR 0.11.1

New functions

• describe_posterior() gains a plot() method, which is a short cut for plot(estimate_density(describe_posterior())).

bayestestR 0.11

Bug fixes

• Fixed issues related to last brms update.

• Fixed bug in describe_posterior.BFBayesFactor() where Bayes factors were missing from out put ( #442 ).

bayestestR 0.10.0

CRAN release: 2021-05-31

Breaking

• All Bayes factors are now returned as log(BF) (column name log_BF). Printing is unaffected. To retrieve the raw BFs, you can run exp(result$log_BF).

New functions

• bci() (and its alias bcai()) to compute bias-corrected and accelerated bootstrap intervals. Along with this new function, ci() and describe_posterior() gain a new ci_method type, "bci".

Changes

• contr.bayes has been renamed contr.orthonorm to be more explicit about its function.

bayestestR 0.9.0

CRAN release: 2021-04-08

Breaking

• The default ci width has been changed to 0.95 instead of 0.89 (see here). This should not come as a surprise to the long-time users of bayestestR as we have been warning about this impending change for a while now :)

• Column names for bayesfactor_restricted() are now p_prior and p_posterior (was Prior_prob and Posterior_prob), to be consistent with bayesfactor_inclusion() output.

• Removed the experimental function mhdior.

General

• Support for blavaan models.

• Support for blrm models (rmsb).

• Support for BGGM models (BGGM).

• check_prior() and describe_prior() should now also work for more ways of prior definition in models from rstanarm or brms.

Bug fixes

• Fixed bug in print() method for the mediation() function.

• Fixed remaining inconsistencies with CI values, which were not reported as fraction for rope().

• Fixed issues with special prior definitions in check_prior(), describe_prior() and simulate_prior().

bayestestR 0.8.2

CRAN release: 2021-01-26

General

• Support for bamlss models.

• Roll-back R dependency to R >= 3.4.

Changes to functions

• All .stanreg methods gain a component argument, to also include auxiliary parameters.

Bug fixes

• bayesfactor_parameters() no longer errors for no reason when computing extremely un/likely direction hypotheses.

• bayesfactor_pointull() / bf_pointull() are now bayesfactor_pointnull() / bf_pointnull() (can you spot the difference? #363 ).

bayestestR 0.8.0

CRAN release: 2020-12-05

New functions

• sexit(), a function for sequential effect existence and significance testing (SEXIT).

General

• Added startup-message to warn users that default ci-width might change in a future update.

• Added support for mcmc.list objects.

Bug fixes

• unupdate() gains a newdata argument to work with brmsfit_multiple models.

• Fixed issue in Bayes factor vignette (don’t evaluate code chunks if packages not available).

bayestestR 0.7.5

CRAN release: 2020-10-22

New functions

• Added as.matrix() function for bayesfactor_model arrays.

• unupdate(), a utility function to get Bayesian models un-fitted from the data, representing the priors only.

Changes to functions

• ci() supports emmeans - both Bayesian and frequentist ( #312 - cross fix with parameters)

Bug fixes

• Fixed issue with default rope range for BayesFactor models.

• Fixed issue in collinearity-check for rope() for models with less than two parameters.

• Fixed issue in print-method for mediation() with stanmvreg-models, which displays the wrong name for the response-value.

• Fixed issue in effective_sample() for models with only one parameter.

• rope_range() for BayesFactor models returns non-NA values ( #343 )

bayestestR 0.7.2

CRAN release: 2020-07-20

New functions

• mediation(), to compute average direct and average causal mediation effects of multivariate response models (brmsfit, stanmvreg).

Bug fixes

• bayesfactor_parameters() works with R<3.6.0.

bayestestR 0.7.0

CRAN release: 2020-06-19

General

• Preliminary support for stanfit objects.

• Added support for bayesQR objects.

Changes to functions

• weighted_posteriors() can now be used with data frames.

• Revised print() for describe_posterior().

• Improved value formatting for Bayesfactor functions.

Bug fixes

• Link transformation are now taken into account for emmeans objets. E.g., in describe_posterior().

• Fix diagnostic_posterior() when algorithm is not “sampling”.

• Minor revisions to some documentations.

• Fix CRAN check issues for win-old-release.

bayestestR 0.6.0

CRAN release: 2020-04-20

Changes to functions

• describe_posterior() now also works on effectsize::standardize_posteriors().

• p_significance() now also works on parameters::simulate_model().

• rope_range() supports more (frequentis) models.

Bug fixes

• Fixed issue with plot() data.frame-methods of p_direction() and equivalence_test().

• Fix check issues for forthcoming insight-update.

bayestestR 0.5.3

CRAN release: 2020-03-26

General

• Support for bcplm objects (package cplm)

Changes to functions

• estimate_density() now also works on grouped data frames.

Bug fixes

• Fixed bug in weighted_posteriors() to properly weight Intercept-only BFBayesFactor models.

• Fixed bug in weighted_posteriors() when models have very low posterior probability ( #286 ).

• Fixed bug in describe_posterior(), rope() and equivalence_test() for brmsfit models with monotonic effect.

• Fixed issues related to latest changes in as.data.frame.brmsfit() from the brms package.

bayestestR 0.5.0

CRAN release: 2020-01-18

General

• Added p_pointnull() as an alias to p_MAP().

• Added si() function to compute support intervals.

• Added weighted_posteriors() for generating posterior samples averaged across models.

• Added plot()-method for p_significance().

• p_significance() now also works for brmsfit-objects.

• estimate_density() now also works for MCMCglmm-objects.

• equivalence_test() gets effects and component arguments for stanreg and brmsfit models, to print specific model components.

• Support for mcmc objects (package coda)

• Provide more distributions via distribution().

• Added distribution_tweedie().

• Better handling of stanmvreg models for describe_posterior(), diagnostic_posterior() and describe_prior().

Breaking changes

• point_estimate(): argument centrality default value changed from ‘median’ to ‘all’.

• p_rope(), previously as exploratory index, was renamed as mhdior() (for Max HDI inside/outside ROPE), as p_rope() will refer to rope(..., ci = 1) ( #258 )

Bug fixes

• Fixed mistake in description of p_significance().

• Fixed error when computing BFs with emmGrid based on some non-linear models ( #260 ).

• Fixed wrong output for percentage-values in print.equivalence_test().

• Fixed issue in describe_posterior() for BFBayesFactor-objects with more than one model.

bayestestR 0.4.0

CRAN release: 2019-10-20

New functions / features

• convert_bayesian_to_frequentist() Convert (refit) Bayesian model as frequentist

• distribution_binomial() for perfect binomial distributions

• simulate_ttest() Simulate data with a mean difference

• simulate_correlation() Simulate correlated datasets

• p_significance() Compute the probability of Practical Significance (ps)

• overlap() Compute overlap between two empirical distributions

• estimate_density(): method = "mixture" argument added for mixture density estimation

Bug fixes

• Fixed bug in simulate_prior() for stanreg-models when autoscale was set to FALSE

bayestestR 0.3.0

CRAN release: 2019-09-22

General

• revised print()-methods for functions like rope(), p_direction(), describe_posterior() etc., in particular for model objects with random effects and/or zero-inflation component

New functions / features

• check_prior() to check if prior is informative

• simulate_prior() to simulate model’s priors as distributions

• distribution_gamma() to generate a (near-perfect or random) Gamma distribution

• contr.bayes function for orthogonal factor coding (implementation from Singmann & Gronau’s bfrms, used for proper prior estimation when factor have 3 levels or more. See Bayes factor vignette ## Changes to functions

• Added support for sim, sim.merMod (from arm::sim()) and MCMCglmm-objects to many functions (like hdi(), ci(), eti(), rope(), p_direction(), point_estimate(), …)

• describe_posterior() gets an effects and component argument, to include the description of posterior samples from random effects and/or zero-inflation component.

• More user-friendly warning for non-supported models in bayesfactor()-methods

Bug fixes

• Fixed bug in bayesfactor_inclusion() where the same interaction sometimes appeared more than once (#223)

• Fixed bug in describe_posterior() for stanreg models fitted with fullrank-algorithm

bayestestR 0.2.5

CRAN release: 2019-08-06

Breaking changes

• rope_range() for binomial model has now a different default (-.18; .18 ; instead of -.055; .055)

• rope(): returns a proportion (between 0 and 1) instead of a value between 0 and 100

• p_direction(): returns a proportion (between 0.5 and 1) instead of a value between 50 and 100 (#168)

• bayesfactor_savagedickey(): hypothesis argument replaced by null as part of the new bayesfactor_parameters() function

New functions / features

• density_at(), p_map() and map_estimate(): method argument added

• rope(): ci_method argument added

• eti(): Computes equal-tailed intervals

• reshape_ci(): Reshape CIs between wide/long

• bayesfactor_parameters(): New function, replacing bayesfactor_savagedickey(), allows for computing Bayes factors against a point-null or an interval-null

• bayesfactor_restricted(): Function for computing Bayes factors for order restricted models

Minor changes

Bug fixes

• bayesfactor_inclusion() now works with R < 3.6.

bayestestR 0.2.2

CRAN release: 2019-06-20

Breaking changes

• equivalence_test(): returns capitalized output (e.g., Rejected instead of rejected)

• describe_posterior.numeric(): dispersion defaults to FALSE for consistency with the other methods

New functions / features

• pd_to_p() and p_to_pd(): Functions to convert between probability of direction (pd) and p-value

• Support of emmGrid objects: ci(), rope(), bayesfactor_savagedickey(), describe_posterior(), …

Minor changes

• Improved tutorial 2

Bug fixes

• describe_posterior(): Fixed column order restoration

• bayesfactor_inclusion(): Inclusion BFs for matched models are more inline with JASP results.

bayestestR 0.2.0

CRAN release: 2019-05-29

Breaking changes

• plotting functions now require the installation of the see package

• estimate argument name in describe_posterior() and point_estimate() changed to centrality

• hdi(), ci(), rope() and equivalence_test() default ci to 0.89

• rnorm_perfect() deprecated in favour of distribution_normal()

• map_estimate() now returns a single value instead of a dataframe and the density parameter has been removed. The MAP density value is now accessible via attributes(map_output)$MAP_density

New functions / features

• describe_posterior(), describe_prior(), diagnostic_posterior(): added wrapper function

• point_estimate() added function to compute point estimates

• p_direction(): new argument method to compute pd based on AUC

• area_under_curve(): compute AUC

• distribution() functions have been added

• bayesfactor_savagedickey(), bayesfactor_models() and bayesfactor_inclusion() functions has been added

• Started adding plotting methods (currently in the see package) for p_direction() and hdi()

• probability_at() as alias for density_at()

• effective_sample() to return the effective sample size of Stan-models

• mcse() to return the Monte Carlo standard error of Stan-models

Minor changes

• Improved documentation

• Improved testing

• p_direction(): improved printing

• rope() for model-objects now returns the HDI values for all parameters as attribute in a consistent way

• Changes legend-labels in plot.equivalence_test() to align plots with the output of the print()-method (#78)

Bug fixes

• hdi() returned multiple class attributes (#72)

• Printing results from hdi() failed when ci-argument had fractional parts for percentage values (e.g. ci = 0.995).

• plot.equivalence_test() did not work properly for brms-models (#76).

bayestestR 0.1.0

CRAN release: 2019-04-08

• CRAN initial publication and 0.1.0 release

• Added a NEWS.md file to track changes to the package