- Revised usage of
`insight::get_data()`

to meet forthcoming changes in the*insight*package.

`check_collinearity()`

now accepts`NULL`

for the`ci`

argument.

- Fixed issue in
`item_difficulty()`

with detecting the maximum values of an item set. Furthermore,`item_difficulty()`

gets a`maximum_value`

argument in case no item contains the maximum value due to missings.

- Minor improvements to the documentation.

`icc()`

and`r2_nakagawa()`

get`ci`

and`iterations`

arguments, to compute confidence intervals for the ICC resp. R2, based on bootstrapped sampling.`r2()`

gets`ci`

, to compute (analytical) confidence intervals for the R2.`check_predictions()`

accepts a`bw`

argument (smoothing bandwidth), which is passed down to the`plot()`

methods density-estimation. The default for the smoothing bandwidth`bw`

has changed from`"nrd0"`

to`"nrd"`

, which seems to produce better fitting plots for non-gaussian models.The model underlying

`check_distribution()`

was now also trained to detect cauchy, half-cauchy and inverse-gamma distributions.`model_performance()`

now allows to include the ICC for Bayesian models.

`verbose`

didn’t work for`r2_bayes()`

with`BFBayesFactor`

objects.Fixed issues in

`check_model()`

for models with convergence issues that lead to`NA`

values in residuals.Fixed bug in

`check_outliers`

whereby passing multiple elements to the threshold list generated an error (#496).`test_wald()`

now warns the user about inappropriate F test and calls`test_likelihoodratio()`

for binomial models.Fixed edge case for usage of

`parellel::detectCores()`

in`check_outliers()`

.

The minimum needed R version has been bumped to

`3.6`

.The alias

`performance_lrt()`

was removed. Use`test_lrt()`

resp.`test_likelihoodratio()`

.

- Following functions were moved from package
*parameters*to*performance*:`check_sphericity_bartlett()`

,`check_kmo()`

,`check_factorstructure()`

and`check_clusterstructure()`

.

`check_normality()`

,`check_homogeneity()`

and`check_symmetry()`

now works for`htest`

objects.Print method for

`check_outliers()`

changed significantly: now states the methods, thresholds, and variables used, reports outliers per variable (for univariate methods) as well as any observation flagged for several variables/methods. Includes a new optional ID argument to add along the row number in the output (@rempsyc #443).`check_outliers()`

now uses more conventional outlier thresholds. The`IQR`

and confidence interval methods now gain improved distance scores that are continuous instead of discrete.

Fixed wrong

*z*-score values when using a vector instead of a data frame in`check_outliers()`

(#476).Fixed

`cronbachs_alpha()`

for objects from`parameters::principal_component()`

.

`print()`

methods for`model_performance()`

and`compare_performance()`

get a`layout`

argument, which can be`"horizontal"`

(default) or`"vertical"`

, to switch the layout of the printed table.Improved speed performance for

`check_model()`

and some other`performance_*()`

functions.Improved support for models of class

`geeglm`

.

`check_model()`

gains a`show_dots`

argument, to show or hide data points. This is particular useful for models with many observations, where generating the plot would be very slow.

- Fixes wrong column names in
`model_performance()`

output for`kmeans`

objects (#453)

- The formerly “conditional” ICC in
`icc()`

is now named “unadjusted” ICC.

`performance_cv()`

for cross-validated model performance.

- Added support for models from package
*estimator*.

`check_overdispersion()`

gets a`plot()`

method.`check_outliers()`

now also works for models of classes`gls`

and`lme`

. As a consequence,`check_model()`

will no longer fail for these models.`check_collinearity()`

now includes the confidence intervals for the VIFs and tolerance values.`model_performance()`

now also includes within-subject R2 measures, where applicable.Improved handling of random effects in

`check_normality()`

(i.e. when argument`effects = "random"`

).

`check_predictions()`

did not work for GLMs with matrix-response.`check_predictions()`

did not work for logistic regression models (i.e. models with binary response) from package*glmmTMB*`item_split_half()`

did not work when the input data frame or matrix only contained two columns.Fixed wrong computation of

`BIC`

in`model_performance()`

when models had transformed response values.Fixed issues in

`check_model()`

for GLMs with matrix-response.

`check_concurvity()`

, which returns GAM concurvity measures (comparable to collinearity checks).

`check_predictions()`

,`check_collinearity()`

and`check_outliers()`

now support (mixed) regression models from`BayesFactor`

.`check_zeroinflation()`

now also works for`lme4::glmer.nb()`

models.`check_collinearity()`

better supports GAM models.

`test_performance()`

now calls`test_lrt()`

or`test_wald()`

instead of`test_vuong()`

when package*CompQuadForm*is missing.`test_performance()`

and`test_lrt()`

now compute the corrected log-likelihood when models with transformed response variables (such as log- or sqrt-transformations) are passed to the functions.

`performance_aic()`

now corrects the AIC value for models with transformed response variables. This also means that comparing models using`compare_performance()`

allows comparisons of AIC values for models with and without transformed response variables.Also,

`model_performance()`

now corrects both AIC and BIC values for models with transformed response variables.

The

`print()`

method for`binned_residuals()`

now prints a short summary of the results (and no longer generates a plot). A`plot()`

method was added to generate plots.The

`plot()`

output for`check_model()`

was revised:For binomial models, the constant variance plot was omitted, and a binned residuals plot included.

The density-plot that showed normality of residuals was replaced by the posterior predictive check plot.

`model_performance()`

for models from*lme4*did not report AICc when requested.`r2_nakagawa()`

messed up order of group levels when`by_group`

was`TRUE`

.

The

`ci`

-level in`r2()`

for Bayesian models now defaults to`0.95`

, to be in line with the latest changes in the*bayestestR*package.S3-method dispatch for

`pp_check()`

was revised, to avoid problems with the*bayesplot*package, where the generic is located.

Minor revisions to wording for messages from some of the check-functions.

`posterior_predictive_check()`

and`check_predictions()`

were added as aliases for`pp_check()`

.

`check_multimodal()`

and`check_heterogeneity_bias()`

. These functions will be removed from the*parameters*packages in the future.

`r2()`

for linear models can now compute confidence intervals, via the`ci`

argument.

Fixed issues in

`check_model()`

for Bayesian models.Fixed issue in

`pp_check()`

for models with transformed response variables, so now predictions and observed response values are on the same (transformed) scale.

`check_outliers()`

has new`ci`

(or`hdi`

,`eti`

) method to filter based on Confidence/Credible intervals.`compare_performance()`

now also accepts a list of model objects.`performance_roc()`

now also works for binomial models from other classes than*glm*.Several functions, like

`icc()`

or`r2_nakagawa()`

, now have an`as.data.frame()`

method.`check_collinearity()`

now correctly handles objects from forthcoming*afex*update.

`performance_mae()`

to calculate the mean absolute error.

Fixed issue with

`"data length differs from size of matrix"`

warnings in examples in forthcoming R 4.2.Fixed issue in

`check_normality()`

for models with sample size larger than

5.000 observations.

Fixed issue in

`check_model()`

for*glmmTMB*models.Fixed issue in

`check_collinearity()`

for*glmmTMB*models with zero-inflation, where the zero-inflated model was an intercept-only model.

Add support for

`model_fit`

(*tidymodels*).`model_performance`

supports*kmeans*models.

Give more informative warning when

`r2_bayes()`

for*BFBayesFactor*objects can’t be calculated.Several

`check_*()`

functions now return informative messages for invalid model types as input.`r2()`

supports`mhurdle`

(*mhurdle*) models.Added

`print()`

methods for more classes of`r2()`

.The

`performance_roc()`

and`performance_accuracy()`

functions unfortunately had spelling mistakes in the output columns:*Sensitivity*was called*Sensivity*and*Specificity*was called*Specifity*. We think these are understandable mistakes :-)

`check_model()`

`check_model()`

gains more arguments, to customize plot appearance.Added option to detrend QQ/PP plots in

`check_model()`

.

`model_performance()`

The

`metrics`

argument from`model_performance()`

and`compare_performance()`

gains a`"AICc"`

option, to also compute the 2nd order AIC.`"R2_adj"`

is now an explicit option in the`metrics`

argument from`model_performance()`

and`compare_performance()`

.

The default-method for

`r2()`

now tries to compute an r-squared for all models that have no specific`r2()`

-method yet, by using following formula:`1-sum((y-y_hat)^2)/sum((y-y_bar)^2))`

The column name

`Parameter`

in`check_collinearity()`

is now more appropriately named`Term`

.

`test_likelihoodratio()`

now correctly sorts models with identical fixed effects part, but different other model parts (like zero-inflation).Fixed incorrect computation of models from inverse-Gaussian families, or Gaussian families fitted with

`glm()`

.Fixed issue in

`performance_roc()`

for models where outcome was not 0/1 coded.Fixed issue in

`performance_accuracy()`

for logistic regression models when`method = "boot"`

.`cronbachs_alpha()`

did not work for`matrix`

-objects, as stated in the docs. It now does.

- Roll-back R dependency to R >= 3.4.

`compare_performance()`

doesn’t return the models’ Bayes Factors, now returned by`test_performance()`

and`test_bf()`

.

`test_vuong()`

, to compare models using Vuong’s (1989) Test.`test_bf()`

, to compare models using Bayes factors.`test_likelihoodratio()`

as an alias for`performance_lrt()`

.`test_wald()`

, as a rough approximation for the LRT.`test_performance()`

, to run the most relevant and appropriate tests based on the input.

`performance_lrt()`

`performance_lrt()`

get an alias`test_likelihoodratio()`

.Does not return AIC/BIC now (as they are not related to LRT

*per se*and can be easily obtained with other functions).Now contains a column with the difference in degrees of freedom between models.

Fixed column names for consistency.

`model_performance()`

- Added more diagnostics to models of class
`ivreg`

.

Revised computation of

`performance_mse()`

, to ensure that it’s always based on response residuals.`performance_aic()`

is now more robust.

Fixed issue in

`icc()`

and`variance_decomposition()`

for multivariate response models, where not all model parts contained random effects.Fixed issue in

`compare_performance()`

with duplicated rows.`check_collinearity()`

no longer breaks for models with rank deficient model matrix, but gives a warning instead.Fixed issue in

`check_homogeneity()`

for`method = "auto"`

, which wrongly tested the response variable, not the residuals.Fixed issue in

`check_homogeneity()`

for edge cases where predictor had non-syntactic names.

`check_collinearity()`

gains a`verbose`

argument, to toggle warnings and messages.

- Fixed examples, now using suggested packages only conditionally.

`model_performance()`

now supports`margins`

,`gamlss`

,`stanmvreg`

and`semLme`

.

`r2_somers()`

, to compute Somers’ Dxy rank-correlation as R2-measure for logistic regression models.`display()`

, to print output from package-functions into different formats.`print_md()`

is an alias for`display(format = "markdown")`

.

`model_performance()`

`model_performance()`

is now more robust and doesn’t fail if an index could not be computed. Instead, it returns all indices that were possible to calculate.`model_performance()`

gains a default-method that catches all model objects not previously supported. If model object is also not supported by the default-method, a warning is given.`model_performance()`

for metafor-models now includes the degrees of freedom for Cochran’s Q.

`performance_mse()`

and`performance_rmse()`

now always try to return the (R)MSE on the response scale.`performance_accuracy()`

now accepts all types of linear or logistic regression models, even if these are not of class`lm`

or`glm`

.`performance_roc()`

now accepts all types of logistic regression models, even if these are not of class`glm`

.`r2()`

for mixed models and`r2_nakagawa()`

gain a`tolerance`

-argument, to set the tolerance level for singularity checks when computing random effect variances for the conditional r-squared.

Fixed issue in

`icc()`

introduced in the last update that make`lme`

-models fail.Fixed issue in

`performance_roc()`

for models with factors as response.

- Column names for
`model_performance()`

and`compare_performance()`

were changed to be in line with the*easystats*naming convention:`LOGLOSS`

is now`Log_loss`

,`SCORE_LOG`

is`Score_log`

and`SCORE_SPHERICAL`

is now`Score_spherical`

.

`r2_posterior()`

for Bayesian models to obtain posterior distributions of R-squared.

`r2_bayes()`

works with Bayesian models from`BayesFactor`

( #143 ).`model_performance()`

works with Bayesian models from`BayesFactor`

( #150 ).`model_performance()`

now also includes the residual standard deviation.Improved formatting for Bayes factors in

`compare_performance()`

.`compare_performance()`

with`rank = TRUE`

doesn’t use the`BF`

values when`BIC`

are present, to prevent “double-dipping” of the BIC values (#144).The

`method`

argument in`check_homogeneity()`

gains a`"levene"`

option, to use Levene’s Test for homogeneity.

- Fix bug in
`compare_performance()`

when`...`

arguments were function calls to regression objects, instead of direct function calls.

`r2()`

and`icc()`

support`semLME`

models (package*smicd*).`check_heteroscedasticity()`

should now also work with zero-inflated mixed models from*glmmTMB*and*GLMMadpative*.`check_outliers()`

now returns a logical vector. Original numerical vector is still accessible via`as.numeric()`

.

`pp_check()`

to compute posterior predictive checks for frequentist models.

Fixed issue with incorrect labeling of groups from

`icc()`

when`by_group = TRUE`

.Fixed issue in

`check_heteroscedasticity()`

for mixed models where sigma could not be calculated in a straightforward way.Fixed issues in

`check_zeroinflation()`

for`MASS::glm.nb()`

.Fixed CRAN check issues.

- Removed suggested packages that have been removed from CRAN.

`icc()`

now also computes a “classical” ICC for`brmsfit`

models. The former way of calculating an “ICC” for`brmsfit`

models is now available as new function called`variance_decomposition()`

.

Fix issue with new version of

*bigutilsr*for`check_outliers()`

.Fix issue with model order in

`performance_lrt()`

.

- Support for models from package
*mfx*.

`model_performance.rma()`

now includes results from heterogeneity test for meta-analysis objects.`check_normality()`

now also works for mixed models (with the limitation that studentized residuals are used).`check_normality()`

gets an`effects`

-argument for mixed models, to check random effects for normality.

Fixed issue in

`performance_accuracy()`

for binomial models when response variable had non-numeric factor levels.Fixed issues in

`performance_roc()`

, which printed 1 - AUC instead of AUC.

Minor revisions to

`model_performance()`

to meet changes in*mlogit*package.Support for

`bayesx`

models.

`icc()`

gains a`by_group`

argument, to compute ICCs per different group factors in mixed models with multiple levels or cross-classified design.`r2_nakagawa()`

gains a`by_group`

argument, to compute explained variance at different levels (following the variance-reduction approach by Hox 2010).`performance_lrt()`

now works on*lavaan*objects.

Fix issues in some functions for models with logical dependent variable.

Fix bug in

`check_itemscale()`

, which caused multiple computations of skewness statistics.Fix issues in

`r2()`

for*gam*models.

`model_performance()`

and`r2()`

now support*rma*-objects from package*metafor*,*mlm*and*bife*models.

`compare_performance()`

gets a`bayesfactor`

argument, to include or exclude the Bayes factor for model comparisons in the output.Added

`r2.aov()`

.

Fixed issue in

`performance_aic()`

for models from package*survey*, which returned three different AIC values. Now only the AIC value is returned.Fixed issue in

`check_collinearity()`

for*glmmTMB*models when zero-inflated formula only had one predictor.Fixed issue in

`check_model()`

for*lme*models.Fixed issue in

`check_distribution()`

for*brmsfit*models.Fixed issue in

`check_heteroscedasticity()`

for*aov*objects.Fixed issues for

*lmrob*and*glmrob*objects.