NEWS.md
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"
.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()
.
.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.
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
.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 FALSE
print()
-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)
CRAN initial publication and 0.1.0 release
Added a NEWS.md
file to track changes to the package