`standardize_names()`

was moved to the*insight*package.

- Support for
`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()`

.

`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.

- Added vignette on model parameters and missing data.
- Update citation.

- 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.

- fix issue with rank deficient models.

- We changed the computation of confidence intervals or standard errors, so these are now based on a t-distribution with degrees of freedom and not normal distribution assuming infinite degrees of freedom. This was implemented for most functions before and only affects few functions (like
`equivalence_test()`

or CIs for standardized parameters from`model_parameters()`

when standardization method was`"posthoc"`

).

`averaging`

(*MuMIn*),`bayesx`

(*R2BayesX*),`afex_aov`

(*afex*)

`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()`

.

- Remove ‘Zelig’ from suggested packages, as it was removed from CRAN.

`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()`

.

- Fixed
`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.

- Added support for
`arima`

(*stats*),`bife`

(*bife*),`bcplm`

and`zcpglm`

(*cplm*)

- 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.

`skewness()`

now uses a different method to calculate the skewness by default. Different methods can be selected using the`type`

-argument.`kurtosis()`

now uses a different method to calculate the skewness by default. Different methods can be selected using the`type`

-argument.

- Added support for
`cglm`

(*cglm*),`DirichletRegModel`

(*DirichletReg*)

- Added new vignettes on ‘Standardized Model Parameters’ and ‘Robust Estimation of Standard Errors’, and vignettes are now also published on CRAN.
- Improved handling of robust statistics in
`model_parameters()`

. This should now work for more models than before. - Improved accuracy of
`ci.merMod()`

for`method = "satterthwaite"`

and`method = "kenward"`

. `select_parameters()`

for*stanreg*models, which was temporarily removed due to the CRAN removal of package**projpred**, is now re-implemented.

`dof_betwithin()`

to compute degrees of freedom based on a between-within approximation method (and related to that,`p_value_*()`

and`se_*()`

for this method were added as well).`random_parameters()`

that returns information about the random effects such as variances, R2 or ICC.`closest_component()`

as a small helper that returns the component index for each variable in a data frame that was used in`principal_components()`

.`get_scores()`

as a small helper to extract scales and calculate sum scores from a principal component analysis (PCA,`principal_components()`

).

`n_clusters()`

gets the option`"M3C"`

for the`package`

-argument, so you can try to determine the number of cluster by using the`M3C::M3C()`

function.- The
`print()`

-method for`model_parameters()`

gets a`select`

-argument, to print only selected columns of the parameters table. `model_parameters()`

for meta-analysis models has an improved`print()`

-method for subgroups (see examples in`?model_parameters.rma`

).`model_parameters()`

for mixed models gets a`details`

-argument to additionally print information about the random effects.`model_parameters()`

now accepts the`df_method`

-argument for more (mixed) models.- The Intercept-parameter in
`model_parameters()`

for meta-analysis models was renamed to`"Overall"`

. `skewness()`

gets a`type`

-argument, to compute different types of skewness.`kurtosis()`

gets a`type`

-argument, to compute different types of skewness.`describe_distribution()`

now also works on data frames and gets a nicer print-method.

- Fixed issue in
`model_parameters()`

when`robust = TRUE`

, which could sometimes mess up order of the statistic column. - Fixed issues in
`model_parameters()`

with wrong`df`

for`lme`

-models. - Fixed issues in
`model_parameters.merMod()`

when`df_method`

was not set to default. - Fixed issues in
`model_parameters.merMod()`

and`model_parameters.gee()`

when`robust = TRUE`

. - Fixed issues with
*coxph*models with only one parameter. - Fixed issue in
`format_p()`

when argument`digits`

was`"apa"`

. - Fixed issues in
`model_parameters()`

for`zeroinfl`

-models.

- Fix CRAN check issues, caused by removal of package ‘projpred’.