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.
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().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.
bayesian_as_frequentist() for
brms models with 0 + Intercept specification in
the model formula.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.
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.
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.
as.logical() for bayesfactor_restricted()
results, extracts the boolean vector(s) the mark which draws are part of
the order restriction.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.
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.
p_to_bf(), to convert p-values into Bayes factors. For
more accurate approximate Bayes factors, use
bic_to_bf().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.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.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").
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.
bci() for some objects incorrectly returned the
equal-tailed intervals.describe_posterior() gains a plot()
method, which is a short cut for
plot(estimate_density(describe_posterior())).Fixed issues related to last brms update.
Fixed bug in describe_posterior.BFBayesFactor()
where Bayes factors were missing from out put ( #442 ).
log(BF) (column
name log_BF). Printing is unaffected. To retrieve the raw
BFs, you can run exp(result$log_BF).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".contr.bayes has been renamed
contr.orthonorm to be more explicit about its
function.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.
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.
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().
Support for bamlss models.
Roll-back R dependency to R >= 3.4.
.stanreg methods gain a component
argument, to also include auxiliary parameters.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
).
sexit(), a function for sequential effect existence and
significance testing (SEXIT).Added startup-message to warn users that default ci-width might change in a future update.
Added support for mcmc.list objects.
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).
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.
ci() supports emmeans - both Bayesian and
frequentist ( #312 - cross fix with parameters)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 )
mediation(), to compute average direct and average
causal mediation effects of multivariate response models
(brmsfit, stanmvreg).bayesfactor_parameters() works with
R<3.6.0.Preliminary support for stanfit objects.
Added support for bayesQR objects.
weighted_posteriors() can now be used with data
frames.
Revised print() for
describe_posterior().
Improved value formatting for Bayesfactor functions.
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.
describe_posterior() now also works on
effectsize::standardize_posteriors().
p_significance() now also works on
parameters::simulate_model().
rope_range() supports more (frequentis)
models.
Fixed issue with plot()
data.frame-methods of p_direction() and
equivalence_test().
Fix check issues for forthcoming insight-update.
estimate_density() now also works on grouped data
frames.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.
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().
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 )
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.
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
simulate_prior() for stanreg-models when
autoscale was set to FALSEprint()-methods for functions like
rope(), p_direction(),
describe_posterior() etc., in particular for model objects
with random effects and/or zero-inflation componentcheck_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
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
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
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
bayesfactor_inclusion() now works with
R < 3.6.equivalence_test(): returns capitalized output
(e.g., Rejected instead of rejected)
describe_posterior.numeric():
dispersion defaults to FALSE for consistency
with the other methods
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(), …
describe_posterior(): Fixed column order
restoration
bayesfactor_inclusion(): Inclusion BFs for matched
models are more inline with JASP results.
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
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
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)
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).
CRAN initial publication and 0.1.0 release
Added a NEWS.md file to track changes to the
package