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.

Removed

`logLik.felm()`

, because this method is now implemented in the*lfe*package.Support for

`DirichletRegModel`

models.

`check_itemscale()`

to describe various measures of internal consistencies for scales which were built from several items from a PCA, using`parameters::principal_components()`

.`r2_efron()`

to compute Efron’s pseudo R2.

- Fixed issue in documentation of
`performance_score()`

.

- Support for
`mixor`

,`cpglm`

and`cpglmm`

models.

`performance_aic()`

as a small wrapper that returns the AIC. It is a generic function that also works for some models that don’t have a AIC method (like Tweedie models).`performance_lrt()`

as a small wrapper around`anova()`

to perform a Likelihood-Ratio-Test for model comparison.

- Fix issues with CRAN checks.

`model_performance()`

now calculates AIC for Tweedie models.

Support for

`bracl`

,`brmultinom`

,`fixest`

,`glmx`

,`glmmadmb`

,`mclogit`

,`mmclogit`

,`vgam`

and`vglm`

models.`model_performance()`

now supports*plm*models.`r2()`

now supports*complmrob*models.`compare_performance()`

now gets a`plot()`

-method (requires package**see**).

`compare_performance()`

gets a`rank`

-argument, to rank models according to their overall model performance.`compare_performance()`

has a nicer`print()`

-method now.Verbosity for

`compare_performance()`

was slightly adjusted.`model_performance()`

-methods for different objects now also have a`verbose`

-argument.

`check_collinearity()`

now no longer returns backticks in row- and column names.

Fixed issue in

`r2()`

for`wbm`

-models with cross-level interactions.`plot()`

-methods for`check_heteroscedasticity()`

and`check_homogeneity()`

now work without requiring to load package*see*before.Fixed issues with models of class

`rlmerMod`

.

`performance()`

is an alias for`model_performance()`

.

`principal_components()`

was removed and re-implemented in the**parameters**-package. Please use`parameters::principal_components()`

now.

`check_outliers()`

now also works on data frames.Added more methods to

`check_outliers()`

.`performance_score()`

now also works on`stan_lmer()`

and`stan_glmer()`

objects.`check_singularity()`

now works with models of class*clmm*.`r2()`

now works with models of class*clmm*,*bigglm*and*biglm*.`check_overdispersion()`

for mixed models now checks that model family is Poisson.

Fixed bug in

`compare_performance()`

that toggled a warning although models were fit from same data.Fixed bug in

`check_model()`

for*glmmTMB*models that occurred when checking for outliers.

Many

`check_*()`

-methods now get a`plot()`

-method. Package**see**is required for plotting.`model_performance()`

gets a preliminary`print()`

-method.

The attribute for the standard error of the Bayesian R2 (

`r2_bayes()`

) was renamed from`std.error`

to`SE`

to be in line with the naming convention of other easystats-packages.`compare_performance()`

now shows the Bayes factor when all compared models are fit from the same data. Previous behaviour was that the BF was shown when models were of same class.

`model_performance()`

now also works for*lavaan*-objects.`check_outliers()`

gets a`method`

-argument to choose the method for detecting outliers. Furthermore, two new methods (Mahalanobis Distance and Invariant Coordinate Selection) were implemented.`check_model()`

now performs more checks for GLM(M)s and other model objects.`check_model()`

gets a`check`

-argument to plot selected checks only.`r2_nakagawa()`

now returns r-squared for models with singular fit, where no random effect variances could be computed. The r-squared then does not take random effect variances into account. This behaviour was changed to be in line with`MuMIn::r.squaredGLMM()`

, which returned a value for models with singular fit.`check_distribution()`

now detects negative binomial and zero-inflated distributions. Furthermore, attempt to improve accuracy.`check_distribution()`

now also accepts a numeric vector as input.`compare_performance()`

warns if models were not fit from same data.

`check_homogeneity()`

to check models for homogeneity of variances.

Fixed issues with

`compare_performance()`

and row-ordering.Fixed issue in

`check_collinearity()`

for zero-inflated models, where the zero-inflation component had not enough model terms to calculate multicollinearity.Fixed issue in some

`check_*()`

and`performance_*()`

functions for models with binary outcome, when outcome variable was a factor.

`r2()`

now works for more regression models.`r2_bayes()`

now works for multivariate response models.`model_performance()`

now works for more regression models, and also includes the log-loss, proper scoring rules and percentage of correct predictions as new metric for models with binary outcome.

`performance_accuracy()`

, which calculates the predictive accuracy of linear or logistic regression models.`performance_logloss()`

to compute the log-loss of models with binary outcome. The log-loss is a proper scoring function comparable to the`rmse()`

.`performance_score()`

to compute the logarithmic, quadratic and spherical proper scoring rules.`performance_pcp()`

to calculate the percentage of correct predictions for models with binary outcome.`performance_roc()`

, to calculate ROC-curves.`performance_aicc()`

, to calculate the second-order AIC (AICc).

`check_collinearity()`

to calculate the variance inflation factor and check model predictors for multicollinearity.`check_outliers()`

to check models for influential observations.`check_heteroscedasticity()`

to check models for (non-)constant error variance.`check_normality()`

to check models for (non-)normality of residuals.`check_autocorrelation()`

to check models for auto-correlated residuals.`check_distribution()`

to classify the distribution of a model-family using machine learning.

`r2_mckelvey()`

to compute McKelvey and Zavoinas R2 value.`r2_zeroinflated()`

to compute R2 for zero-inflated (non-mixed) models.`r2_xu()`

as a crude R2 measure for linear (mixed) models.

`model_performance.stanreg()`

and`model_performance.brmsfit()`

now only return one R2-value and its standard error, instead of different (robust) R2 measures and credible intervals.`error_rate()`

is now integrated in the`performance_pcp()`

-function.

`model_performance.stanreg()`

and`model_performance.brmsfit()`

now also return the*WAIC*(widely applicable information criterion).`r2_nakagawa()`

now calculates the full R2 for mixed models with zero-inflation.`icc()`

now returns`NULL`

and no longer stops when no mixed model is provided.`compare_performance()`

now shows the Bayes factor when all compared models are of same class.Some functions get a

`verbose`

-argument to show or suppress warnings.

Renamed

`r2_coxnell()`

to`r2_coxsnell()`

.Fix issues in

`r2_bayes()`

and`model_performance()`

for ordinal models resp. models with cumulative link (#48).`compare_performance()`

did not sort the`name`

-column properly, if the columns`class`

and`name`

were not in the same alphabetical order (#51).