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.model_performance() output
for kmeans objects (#453)icc() is now named
“unadjusted” ICC.performance_cv() for cross-validated model
performance.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.
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()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.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.
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.
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.
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().
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.