NEWS.md
model_parameters()
, in particular for glm’s.model_parameters()
for merMod
models now also computes CIs for the random SD parameters when ci_method="boot"
(previously, this was only possible when ci_method
was "profile"
).
model_parameters()
for glmmTMB
models now computes CIs for the random SD parameters. Note that these are based on a Wald-z-distribution.
Similar to model_parameters.htest()
, the model_parameters.BFBayesFactor()
method gains cohens_d
and cramers_v
arguments to control if you need to add frequentist effect size estimates to the returned summary dataframe. Previously, this was done by default.
Fixed bug with ci()
for class merMod
when method="boot"
.
Fixed issue with correct association of components for ordinal models of classes clm
and clm2
.
Fixed issues in random_parameters()
and model_parameters()
for mixed models without random intercept.
Confidence intervals for random parameters in model_parameters()
failed for (some?) glmer
models.
Following functions were moved to the new datawizard package and are now re-exported from parameters package:
data_partition()
demean()
(and its aliases degroup()
and detrend()
)
skewness()
Note that these functions will be removed in the next release of parameters package and they are currently being re-exported only as a convenience for the package developers. This release should provide them with time to make the necessary changes before this breaking change is implemented.
Following functions were moved to the performance package:
The handling to approximate the degrees of freedom in model_parameters()
, ci()
and p_value()
was revised and should now be more consistent. Some bugs related to the previous computation of confidence intervals and p-values have been fixed. Now it is possible to change the method to approximate degrees of freedom for CIs and p-values using the ci_method
, resp. method
argument. This change has been documented in detail in ?model_parameters
, and online here: https://easystats.github.io/parameters/reference/model_parameters.html
Minor changes to print()
for glmmTMB with dispersion parameter.
Added vignette on printing options for model parameters.
model_parameters()
The df_method
argument in model_parameters()
is deprecated. Please use ci_method
now.
model_parameters()
with standardize = "refit"
now returns random effects from the standardized model.
model_parameters()
and ci()
for lmerMod
models gain a "residuals"
option for the ci_method
(resp. method
) argument, to explicitly calculate confidence intervals based on the residual degrees of freedom, when present.
model_parameters()
supports following new objects: trimcibt
, wmcpAKP
, dep.effect
(in WRS2 package), systemfit
model_parameters()
gains a new argument table_wide
for ANOVA tables. This can be helpful for users who may wish to report ANOVA table in wide format (i.e., with numerator and denominator degrees of freedom on the same row).
model_parameters()
gains two new arguments, keep
and drop
. keep
is the new names for the former parameters
argument and can be used to filter parameters. While keep
selects those parameters whose names match the regular expression pattern defined in keep
, drop
is the counterpart and excludes matching parameter names.
When model_parameters()
is called with verbose = TRUE
, and ci_method
is not the default value, the printed output includes a message indicating which approximation-method for degrees of freedom was used.
model_parameters()
for mixed models with ci_method = "profile
computes (profiled) confidence intervals for both fixed and random effects. Thus, ci_method = "profile
allows to add confidence intervals to the random effect variances.
model_parameters()
should longer fail for supported model classes when robust standard errors are not available.
n_factors()
the methods based on fit indices have been fixed and can be included separately (package = "fit"
). Also added a n_max
argument to crop the output.
compare_parameters()
now also accepts a list of model objects.
describe_distribution()
gets verbose
argument to toggle warnings and messages.
format_parameters()
removes dots and underscores from parameter names, to make these more “human readable”.
The experimental calculation of p-values in equivalence_test()
was replaced by a proper calculation p-values. The argument p_value
was removed and p-values are now always included.
Minor improvements to print()
, print_html()
and print_md()
.
The random effects returned by model_parameters()
mistakenly displayed the residuals standard deviation as square-root of the residual SD.
Fixed issue with model_parameters()
for brmsfit objects that model standard errors (i.e. for meta-analysis).
Fixed issue in model_parameters
for lmerMod
models that, by default, returned residual degrees of freedom in the statistic column, but confidence intervals were based on Inf
degrees of freedom instead.
Fixed issue in ci_satterthwaite()
, which used Inf
degrees of freedom instead of the Satterthwaite approximation.
Fixed issue in model_parameters.mlm()
when model contained interaction terms.
Fixed issue in model_parameters.rma()
when model contained interaction terms.
Fixed sign error for model_parameters.htest()
for objects created with t.test.formula()
(issue #552)
Fixed issue when computing random effect variances in model_parameters()
for mixed models with categorical random slopes.
check_sphericity()
has been renamed into check_sphericity_bartlett()
.
Removed deprecated arguments.
model_parameters()
for bootstrapped samples used in emmeans now treats the bootstrap samples as samples from posterior distributions (Bayesian models).
SemiParBIV
(GJRM), selection
(sampleSelection), htest
from the survey package, pgmm
(plm).summary()
method for model_parameters()
, which is a convenient shortcut for print(..., select = "minimal")
.model_parameters()
model_parameters()
gains a parameters
argument, which takes a regular expression as string, to select specific parameters from the returned data frame.
print()
for model_parameters()
and compare_parameters()
gains a groups
argument, to group parameters in the output. Furthermore, groups
can be used directly as argument in model_parameters()
and compare_parameters()
and will be passed to the print()
method.
model_parameters()
for ANOVAs now saves the type as attribute and prints this information as footer in the output as well.
model_parameters()
for htest-objects now saves the alternative hypothesis as attribute and prints this information as footer in the output as well.
model_parameters()
passes arguments type
, parallel
and n_cpus
down to bootstrap_model()
when bootstrap = TRUE
.
bootstrap_models()
for merMod and glmmTMB objects gains further arguments to set the type of bootstrapping and to allow parallel computing.
bootstrap_parameters()
gains the ci_method
type "bci"
, to compute bias-corrected and accelerated bootstrapped intervals.
ci()
for svyglm
gains a method
argument.
Fixed issue in model_parameters()
for emmGrid objects with Bayesian models.
Arguments digits
, ci_digits
and p_digits
were ignored for print()
and only worked when used in the call to model_parameters()
directly.
print()
method for model_parameters()
.blrm
(rmsb), AKP
, med1way
, robtab
(WRS2), epi.2by2
(epiR), mjoint
(joineRML), mhurdle
(mhurdle), sarlm
(spatialreg), model_fit
(tidymodels), BGGM
(BGGM), mvord
(mvord)model_parameters()
model_parameters()
for blavaan
models is now fully treated as Bayesian model and thus relies on the functions from bayestestR (i.e. ROPE, Rhat or ESS are reported) .
The effects
-argument from model_parameters()
for mixed models was revised and now shows the random effects variances by default (same functionality as random_parameters()
, but mimicking the behaviour from broom.mixed::tidy()
). When the group_level
argument is set to TRUE
, the conditional modes (BLUPs) of the random effects are shown.
model_parameters()
for mixed models now returns an Effects
column even when there is just one type of “effects”, to mimic the behaviour from broom.mixed::tidy()
. In conjunction with standardize_names()
users can get the same column names as in tidy()
for model_parameters()
objects.
model_parameters()
for t-tests now uses the group values as column names.
print()
for model_parameters()
gains a zap_small
argument, to avoid scientific notation for very small numbers. Instead, zap_small
forces to round to the specified number of digits.
To be internally consistent, the degrees of freedom column for lqm(m)
and cgam(m)
objects (with t-statistic) is called df_error
.
model_parameters()
gains a summary
argument to add summary information about the model to printed outputs.
Minor improvements for models from quantreg.
model_parameters
supports rank-biserial, rank epsilon-squared, and Kendall’s W as effect size measures for wilcox.test()
, kruskal.test
, and friedman.test
, respectively.
describe_distribution()
gets a quartiles
argument to include 25th and 75th quartiles of a variable.Fixed issue with non-initialized argument style
in display()
for compare_parameters()
.
Make print()
for compare_parameters()
work with objects that have “simple” column names for confidence intervals with missing CI-level (i.e. when column is named "CI"
instead of, say, "95% CI"
).
Fixed issue with p_adjust
in model_parameters()
, which did not work for adjustment-methods "BY"
and "BH"
.
Fixed issue with show_sigma
in print()
for model_parameters()
.
Fixed issue in model_parameters()
with incorrect order of degrees of freedom.
Roll-back R dependency to R >= 3.4.
Bootstrapped estimates (from bootstrap_model()
or bootstrap_parameters()
) can be passed to emmeans
to obtain bootstrapped estimates, contrasts, simple slopes (etc) and their CIs.
model_parameters()
and related functions to obtain standard errors, p-values, etc.model_parameters()
now always returns the confidence level for as additional CI
column.
The rule
argument in equivalenct_test()
defaults to "classic"
.
crr
(cmprsk), leveneTest()
(car), varest
(vars), ergm
(ergm), btergm
(btergm), Rchoice
(Rchoice), garch
(tseries)compare_parameters()
(and its alias compare_models()
) to show / print parameters of multiple models in one table.Estimation of bootstrapped p-values has been re-written to be more accurate.
model_parameters()
for mixed models gains an effects
-argument, to return fixed, random or both fixed and random effects parameters.
Revised printing for model_parameters()
for metafor models.
model_parameters()
for metafor models now recognized confidence levels specified in the function call (via argument level
).
Improved support for effect sizes in model_parameters()
from anova objects.
Fixed edge case when formatting parameters from polynomial terms with many degrees.
Fixed issue with random sampling and dropped factor levels in bootstrap_model()
.
coxr
(coxrobust), coeftest
(lmtest), ivfixed
(ivfixed), ivprobit
(ivprobit), riskRegression
(riskRegression), fitdistr
(MASS), yuen
, t1way
, onesampb
, mcp1
and mcp2
(WRS2), Anova.mlm
(car), rqs
(quantreg), lmodel2
(lmodel2), summary.lm
, PMCMR
, osrt
and trendPMCMR
(PMCMRplus), bamlss
(bamlss).print_html()
as an alias for display(format = "html")
. This allows to print tabular outputs from data frames (as returned by most functions in parameters) into nicely rendered HTML markdown tables.Added more effect size measures to model_parameters()
for htest
objects.
model_parameters()
for anova objects gains a power
argument, to calculate the power for each parameter.
ci()
for models from lme4 and glmmTMB can now computed profiled confidence intervals, using method = "profile"
. Consequently, model_parameters()
with df_method = "profile"
also computes profiled confidence intervals. For models of class glmmTMB
, option "uniroot"
is also available.
model_parameters()
for t-tests when standardize_d = TRUE
, did not return columns for the group-specific means.
Fixed issue in p_value()
for fixest::feols()
.
Fixed issue in model_parameters()
for glmer()
models with p-values that were calculated with df_method = "ml1"
or df_method = "betwithin"
.
Fixed issue in model_parameters()
for multinomial models when response was a character vector (and no factor).
Fixed issue in print_md()
for model-parameters objects from Bayesian models.
Fixed issues with printing of model parameters for multivariate response models from brms.
Fixed issue with paired t-tests and model_parameters()
.
format_p_adjust()
, to create pretty names for p-adjustment methods.Fixed breaking code / failing tests due to latest effectsize update.
Fixed issue with model_parameters()
for models of class mlm
.
Undocumented arguments digits
, ci_digits
and p_digits
worked for print()
, but not when directly called inside model_parameters()
. Now, model_parameters(model, digits = 5, ci_digits = 8)
works again.
Fixed some minor printing-issues.
The default-method for effect sizes in model_parameters()
for Anova-models (i.e. when arguments omega_squared
, eta_squared
or epsilon_squared
are set to TRUE
) is now "partial"
, as initially intended.
Column names for degrees of freedom were revised. "df_residual"
was replaced by the more generic "df_error"
. Moreover, models of class htest
now also have the column name "df_error"
and no longer "df"
(where applicable).
Some re-exports for functions that were moved to insight longer ago, were now removed.
Glm
(rms), mediate
(mediation).
model_parameters()
supports Gam
models (gam), ridgelm
(MASS), htest
objects from oneway.test()
, chisq.test()
, prop.test()
, mcnemar.test()
and pairwise.htest
objects, mcmc.list
(e.g. from bayesGARCH).
display()
, to format output from package-functions into different formats.
print_md()
as an alias for display(format = "markdown")
. This allows to print tabular outputs from data frames (as returned by most functions in parameters) into nicely rendered markdown tables.
format()
, to create a “pretty data frame” with nicer column names and formatted values. This is one of the worker-functions behind print()
or print_md()
.
model_parameters()
model_parameters()
for Anova-models (of class aov
, anova
etc.) gains a ci
-argument, to add confidence intervals to effect size parameters.
model_parameters()
for htest
objects gains a cramers_v
and phi
argument, to compute effect size parameters for objects from chisq.test()
, and a standardized_D
argument, to compute effect size parameters for objects from t.test()
.
model_parameters()
for metafor
-models is more stable when called from inside functions.
model_parameters()
for metaBMA-models now includes prior information for the meta-parameters.
model_parameters()
for meta-analysis-models gains a include_studies
-argument, to include or remove studies from the output.
model_parameters()
for gam-models now includes the residual df for smooth terms, and no longer the reference df.
Slightly revised and improved the print()
method for model_parameters()
.
describe_distribution()
now includes the name of the centrality index in the CI
-column, when centrality = "all"
.
pool_parameters()
gains a details
-argument. For mixed models, and if details = TRUE
, random effect variances will also be pooled.
Fixed issue in ci()
for lme models with non-positive definite variance-covariance.
Fixed issue in model_parameters()
for nnet::multinom()
, lqmm::lqm()
, mgcv::gam()
, and margins::margins()
models, and models from package blme.
maov
(stats), HLfit
(spaMM), scam
(scam), preliminary support for emm_list
(emmeans), merModList
(merTools), meta_random
, meta_bma
and meta_fixed
(metaBMA).pool_parameters()
, to pool parameters estimates from multiple models.
degroup()
, as a more generic case for demean()
.
center()
, to center variables.
Better support for (weighted) multivariate response models of class mlm
for functions like model_parameters()
or simulate_parameters()
.
standardize_names()
is now re-exported from the insight package.
print()
for model_parameters()
now names the coefficients column depending on the model type (i.e. "Odds Ratios"
for logistic regression when exponentiate = TRUE
etc.)
print()
for model_parameters()
gains a show_sigma
argument, to show or hide information on the residual standard deviation.
print()
for model_parameters()
displays a message for Bayesian models, indicating which method to compute credible intervals was used.
data_partition()
gets a seed
argument, to explicitly set the seed before random sampling of test and training data.
Revised parameters_table()
, to improve readability of printed output.
Fixed issues in model_parameters()
for vgam and mira objects.
Fixed issue where model_parameters()
for emmGrid objects falsely removed the Coefficient
column.
Fixed issue in parameters_type()
for factors with different effects-coding than treatment contrasts.
Fixed issues due to latest effectsize update.
Fixed issues with glmmTMB models with dispersion-parameter.
Fixed issue where model_parameters()
for glmmTMB models falsely removed the Component
column.
Fixed issue with missing CI columns in model_parameters()
when standardize
was one of the options except "refit"
.
parameters_type()
did not correctly detect interaction terms for specific patterns like scale()
included in the interaction.
Support for mipo
(mice), lqm
and lqmm
(lqmm). Preliminary support for semLME
(smicd), mle2
(bbmle), mle
(stats4)
model_parameters()
for objects of class mira
(mice).
model_parameters()
gets a specific behaviour for brms-meta-analysis models.
model_parameters()
for lavaan and blavaan now also prints self-defined parameters.
model_parameters()
for lavaan and blavaan gains more option for standardized parameters.
Fix issue in model_parameters()
for coxph.penal
models.
Fix issue in model_parameters.metaplus()
with random effects.
Fix issue in check_heterogeneity()
when x
was a mixed model.
Fix issue in check_heterogeneity()
for data with missing values.
Fix issue in dof_ml1()
when random-effect terms where character vectors.
Fix issue in print()
method for model_parameters()
that printed empty lines for rows with complete missing values. Empty lines are now removed.
Fix issue in parameters_type()
when exp()
was used in a model formula.
metaplus
(metaplus), glht
(multcomp), glmm
(glmm), manova
(stats), crq
and crqs
(quantreg)
Improved support for models from the rms package.
Improved parameters formatting for ordered factors in model_parameters()
(and format_parameters()
).
Argument df_method
can now also be applied to GLMs, to allow calculation of confidence intervals based on Wald-approximation, not profiled confidence intervals. This speeds up computation of CIs for models fit to large data sets.
Improved select_parameters()
for mixed models, and revised docs and associated vignette.
Allow threshold
to be passed to efa_to_cfa()
when the model is from factor_analysis()
.
Allow correlation matrix to be passed to factor_analysis()
.
Fix CRAN check issues.
Fix issue in model_parameters()
for models with non-estimable parameters or statistics.
Fix issue in model_parameters()
for plm models with only one parameter.
Fix issue in check_heterogeneity()
in case no predictor would cause heterogeneity bias.
Make sure clubSandwich is used conditionally in all places, to properly pass CRAN checks.
robmixglm
(robmixglm), betaor
, betamfx
, logitor
, poissonirr
, negbinirr
, logitmfx
, probitmfx
, poissonmfx
, negbinmfx
(mfx), partial support emmGrid
(emmeans)simulate_parameters()
and simulate_model()
has a nicer print()
method.
now also simulate parameters from the dispersion model for glmmTMB objects.
gets a verbose
argument, to show or hide warnings and messages.
equivalence_test()
or CIs for standardized parameters from model_parameters()
when standardization method was "posthoc"
).check_heterogeneity()
as a small helper to find variables that have a within- and between-effect related to a grouping variable (and thus, may result in heterogeneity bias, see this vignette).equivalence_test()
gains a rule
argument, so equivalence testing can be based on different approaches.
for mixed models gains an effect
argument, to perform equivalence testing on random effects.
gains a p_values
argument, to calculate p-values for the equivalence test.
now supports more frequentist model objects.
describe_distribution()
now works on grouped data frames.
gains ci
and iterations
arguments, to compute confidence intervals based on bootstrapping.
gains a iqr
argument, to compute the interquartile range.
SE
column was removed.
model_parameters()
model_parameters()
for Stan-models (brms, rstanarm) gains a group_level
argument to show or hide parameters for group levels of random effects.
Improved accuracy of confidence intervals in model_parameters()
with standardize = "basic"
or standardize = "posthoc"
.
model_parameters.merMod()
no longer passes ...
down to bootstrap-functions (i.e. when bootstrap = TRUE
), as this might conflict with lme4::bootMer()
.
For ordinal models (like MASS::polr()
or ordinal::clm()
), a Component
column is added, indicating intercept categories ("alpha"
) and estimates ("beta"
).
The select
-argument from print.parameters_model()
now gets a "minimal"
-option as shortcut to print coefficients, confidence intervals and p-values only.
parameters_table()
and print.parameters_model()
now explicitly get arguments to define the digits for decimal places used in output.
ci()
, standard_error()
, p_value()
and model_parameters()
for glmmTMB models now also works for dispersion models.
Fixed issue in equivalence_test()
for mixed models.
Fixed bug for model_parameters.anova(..., eta_squared = "partial")
when called with non-mixed models.
Fixed issue with wrong degrees of freedom in model_parameters()
for gam models.
Fixed issue with unused arguments in model_parameters()
.
model_parameters()
now also transforms standard errors when exponentiate = TRUE
.
model_parameters()
for anova()
from mixed models can now also compute effect sizes like eta squared.
model_parameters()
for aov()
gains a type
-argument to compute type-1, type-2 or type-3 sums of squares.
model_parameters()
for Bayesian models gains a standardize
argument, to return standardized parameters from the posterior distribution.
Improved print()
method for model_parameters()
for nested aov()
(repeated measurements).
You can now control whether demean()
should add attributes to indicate within- and between-effects. This is only relevant for the print()
-method of model_parameters()
.
model_parameters()
for anova()
from lmerTest models.Alias model_bootstrap()
was removed, please use bootstrap_model()
.
Alias parameters_bootstrap()
was removed, please use bootstrap_parameters()
.
Alias model_simulate()
was removed, please use simulate_model()
.
Alias parameters_simulate()
was removed, please use simulate_parameters()
.
Alias parameters_selection()
was removed, please use select_parameters()
.
Alias parameters_reduction()
was removed, please use reduce_parameters()
.
Functions DDR()
, ICA()
and cmds()
are no longer exported, as these were intended to be used internally by reduce_parameters()
only.
skewness()
and kurtosis()
always return a data frame.
Improved print-method for model_parameters.brmsfit()
.
Improved print-method for model_parameters.merMod()
when fitting REWB-Models (see demean()
).
Improved efficiency for model_parameters()
(for linear mixed models) when df_method = "kenward"
.
model_parameters()
gets a p_adjust
-argument, to adjust p-values for multiple comparisons.
Minor improvements for cluster_analysis()
when method = "kmeans"
and force = TRUE
(factors now also work for kmeans-clustering).
p_value_kenward()
, se_kenward()
etc. now give a warning when model was not fitted by REML.
Added ci()
, standard_error()
and p_value()
for lavaan and blavaan objects.
Added standard_error()
for brmsfit and stanreg objects.
Run certain tests only locally, to reduce duration of CRAN checks.
skewness()
, kurtosis()
and smoothness()
get an iteration
argument, to set the numbers of bootstrap replicates for computing standard errors.
Improved print-method for factor_analysis()
.
demean()
now additionally converts factors with more than 2 levels to dummy-variables (binary), to mimic panelr-behaviour.
Fixed minor issue with the print()
-method for model_parameters.befa()
.
Fixed issues in model_parameters()
(for linear mixed models) with wrong order of degrees of freedom when df_method
was different from default.
Fixed issues in model_parameters()
(for linear mixed models) with accuracy of p-values when df_method = "kenward
.
Fixed issues in model_parameters()
with wrong test statistic for lmerModLmerTest models.
Fixed issue in format_parameters()
(which is used to format output of model_parameters()
) for factors, when variable name was also part of factor levels.
Fixed issue in degrees_of_freedem()
for logistf-models, which unintentionally printed the complete model summary.
Fixed issue in model_parameters()
for mlm models.
Fixed issue in random_parameters()
for uncorrelated random effects.