performance 0.10.4
Changes to functions
icc()
andr2_nakagawa()
gain aci_method
argument, to either calculate confidence intervals usingboot::boot()
(instead oflmer::bootMer()
) whenci_method = "boot"
or analytical confidence intervals (ci_method = "analytical"
). Useci_method = "boot"
when the default method fails to compute confidence intervals and useci_method = "analytical"
if bootstrapped intervals cannot be calculated at all. Note that the default computation method is preferred.check_predictions()
accepts abandwidth
argument (smoothing bandwidth), which is passed down to theplot()
methods density-estimation.check_predictions()
gains atype
argument, which is passed down to theplot()
method to change plot-type (density or discrete dots/intervals). By default,type
is set to"default"
for models without discrete outcomes, and elsetype = "discrete_interval"
.performance_accuracy()
now includes confidence intervals, and reports those by default (the standard error is no longer reported, but still included).
Bug fixes
- Fixed issue in
check_collinearity()
for fixest models that usedi()
to create interactions in formulas.
performance 0.10.3
CRAN release: 2023-04-07
New functions
-
item_discrimination()
, to calculate the discrimination of a scale’s items.
Support for new models
model_performance()
,check_overdispersion()
,check_outliers()
andr2()
now work with objects of classfixest_multi
(@etiennebacher, #554).model_performance()
can now return the “Weak instruments” statistic and p-value for models of classivreg
withmetrics = "weak_instruments"
(@etiennebacher, #560).Support for
mclogit
models.
Changes to functions
test_*()
functions now automatically fit a null-model when only one model objects was provided for testing multiple models.Warnings in
model_performance()
for unsupported objects of classBFBayesFactor
can now be suppressed withverbose = FALSE
.check_predictions()
no longer fails with issues whenre_formula = NULL
for mixed models, but instead gives a warning and tries to compute posterior predictive checks withre_formuka = NA
.check_outliers()
now also works for meta-analysis models from packages metafor and meta.plot()
forperformance::check_model()
no longer produces a normal QQ plot for GLMs. Instead, it now shows a half-normal QQ plot of the absolute value of the standardized deviance residuals.
Bug fixes
- Fixed issue in
print()
method forcheck_collinearity()
, which could mix up the correct order of parameters.
performance 0.10.2
CRAN release: 2023-01-12
General
- Revised usage of
insight::get_data()
to meet forthcoming changes in the insight package.
Changes to functions
-
check_collinearity()
now acceptsNULL
for theci
argument.
Bug fixes
- Fixed issue in
item_difficulty()
with detecting the maximum values of an item set. Furthermore,item_difficulty()
gets amaximum_value
argument in case no item contains the maximum value due to missings.
performance 0.10.1
CRAN release: 2022-11-25
Changes to functions
icc()
andr2_nakagawa()
getci
anditerations
arguments, to compute confidence intervals for the ICC resp. R2, based on bootstrapped sampling.r2()
getsci
, to compute (analytical) confidence intervals for the R2.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.
Bug fixes
verbose
didn’t work forr2_bayes()
withBFBayesFactor
objects.Fixed issues in
check_model()
for models with convergence issues that lead toNA
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 callstest_likelihoodratio()
for binomial models.Fixed edge case for usage of
parellel::detectCores()
incheck_outliers()
.
performance 0.10.0
CRAN release: 2022-10-03
Breaking Change
The minimum needed R version has been bumped to
3.6
.The alias
performance_lrt()
was removed. Usetest_lrt()
resp.test_likelihoodratio()
.
New functions
- Following functions were moved from package parameters to performance:
check_sphericity_bartlett()
,check_kmo()
,check_factorstructure()
andcheck_clusterstructure()
.
Changes to functions
check_normality()
,check_homogeneity()
andcheck_symmetry()
now works forhtest
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. TheIQR
and confidence interval methods now gain improved distance scores that are continuous instead of discrete.
Bug Fixes
Fixed wrong z-score values when using a vector instead of a data frame in
check_outliers()
(#476).Fixed
cronbachs_alpha()
for objects fromparameters::principal_component()
.
performance 0.9.2
CRAN release: 2022-08-10
General
print()
methods formodel_performance()
andcompare_performance()
get alayout
argument, which can be"horizontal"
(default) or"vertical"
, to switch the layout of the printed table.Improved speed performance for
check_model()
and some otherperformance_*()
functions.Improved support for models of class
geeglm
.
Changes to functions
-
check_model()
gains ashow_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.
Bug Fixes
- Fixes wrong column names in
model_performance()
output forkmeans
objects (#453)
performance 0.9.1
CRAN release: 2022-06-20
Breaking
- The formerly “conditional” ICC in
icc()
is now named “unadjusted” ICC.
New functions
-
performance_cv()
for cross-validated model performance.
Changes to functions
check_overdispersion()
gets aplot()
method.check_outliers()
now also works for models of classesgls
andlme
. 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 argumenteffects = "random"
).
Bug fixes
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 glmmTMBitem_split_half()
did not work when the input data frame or matrix only contained two columns.Fixed wrong computation of
BIC
inmodel_performance()
when models had transformed response values.Fixed issues in
check_model()
for GLMs with matrix-response.
performance 0.9.0
CRAN release: 2022-03-30
New functions
-
check_concurvity()
, which returns GAM concurvity measures (comparable to collinearity checks).
Changes to functions
Check functions
check_predictions()
,check_collinearity()
andcheck_outliers()
now support (mixed) regression models fromBayesFactor
.check_zeroinflation()
now also works forlme4::glmer.nb()
models.check_collinearity()
better supports GAM models.
Test functions
test_performance()
now callstest_lrt()
ortest_wald()
instead oftest_vuong()
when package CompQuadForm is missing.test_performance()
andtest_lrt()
now compute the corrected log-likelihood when models with transformed response variables (such as log- or sqrt-transformations) are passed to the functions.
Model performance functions
performance_aic()
now corrects the AIC value for models with transformed response variables. This also means that comparing models usingcompare_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.
Plotting and printing
The
print()
method forbinned_residuals()
now prints a short summary of the results (and no longer generates a plot). Aplot()
method was added to generate plots.-
The
plot()
output forcheck_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.
Bug fixes
model_performance()
for models from lme4 did not report AICc when requested.r2_nakagawa()
messed up order of group levels whenby_group
wasTRUE
.
performance 0.8.0
CRAN release: 2021-10-01
Breaking Changes
The
ci
-level inr2()
for Bayesian models now defaults to0.95
, 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.
General
Minor revisions to wording for messages from some of the check-functions.
posterior_predictive_check()
andcheck_predictions()
were added as aliases forpp_check()
.
New functions
-
check_multimodal()
andcheck_heterogeneity_bias()
. These functions will be removed from the parameters packages in the future.
Changes to functions
-
r2()
for linear models can now compute confidence intervals, via theci
argument.
Bug fixes
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.
performance 0.7.3
CRAN release: 2021-07-21
Changes to functions
check_outliers()
has newci
(orhdi
,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()
orr2_nakagawa()
, now have anas.data.frame()
method.check_collinearity()
now correctly handles objects from forthcoming afex update.
performance 0.7.2
CRAN release: 2021-05-17
New functions
-
performance_mae()
to calculate the mean absolute error.
Bug fixes
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.
performance 0.7.1
CRAN release: 2021-04-09
New supported models
Add support for
model_fit
(tidymodels).model_performance
supports kmeans models.
General
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()
supportsmhurdle
(mhurdle) models.The
performance_roc()
andperformance_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 :-)
Changes to functions
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 frommodel_performance()
andcompare_performance()
gains a"AICc"
option, to also compute the 2nd order AIC."R2_adj"
is now an explicit option in themetrics
argument frommodel_performance()
andcompare_performance()
.
Other functions
The default-method for
r2()
now tries to compute an r-squared for all models that have no specificr2()
-method yet, by using following formula:1-sum((y-y_hat)^2)/sum((y-y_bar)^2))
The column name
Parameter
incheck_collinearity()
is now more appropriately namedTerm
.
Bug fixes
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 whenmethod = "boot"
.cronbachs_alpha()
did not work formatrix
-objects, as stated in the docs. It now does.
performance 0.7.0
CRAN release: 2021-02-03
Breaking Changes
-
compare_performance()
doesn’t return the models’ Bayes Factors, now returned bytest_performance()
andtest_bf()
.
New functions to test or compare models
test_vuong()
, to compare models using Vuong’s (1989) Test.test_bf()
, to compare models using Bayes factors.test_likelihoodratio()
as an alias forperformance_lrt()
.test_wald()
, as a rough approximation for the LRT.test_performance()
, to run the most relevant and appropriate tests based on the input.
Changes to functions
performance_lrt()
performance_lrt()
get an aliastest_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.
Other functions
Revised computation of
performance_mse()
, to ensure that it’s always based on response residuals.performance_aic()
is now more robust.
Bug fixes
Fixed issue in
icc()
andvariance_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()
formethod = "auto"
, which wrongly tested the response variable, not the residuals.Fixed issue in
check_homogeneity()
for edge cases where predictor had non-syntactic names.
performance 0.6.1
CRAN release: 2020-12-09
General
-
check_collinearity()
gains averbose
argument, to toggle warnings and messages.
performance 0.6.0
CRAN release: 2020-12-01
General
-
model_performance()
now supportsmargins
,gamlss
,stanmvreg
andsemLme
.
New functions
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 fordisplay(format = "markdown")
.
Changes to functions
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.
Other functions
performance_mse()
andperformance_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 classlm
orglm
.performance_roc()
now accepts all types of logistic regression models, even if these are not of classglm
.r2()
for mixed models andr2_nakagawa()
gain atolerance
-argument, to set the tolerance level for singularity checks when computing random effect variances for the conditional r-squared.
Bug fixes
Fixed issue in
icc()
introduced in the last update that makelme
-models fail.Fixed issue in
performance_roc()
for models with factors as response.
performance 0.5.1
CRAN release: 2020-10-29
Breaking changes
- Column names for
model_performance()
andcompare_performance()
were changed to be in line with the easystats naming convention:LOGLOSS
is nowLog_loss
,SCORE_LOG
isScore_log
andSCORE_SPHERICAL
is nowScore_spherical
.
New functions
-
r2_posterior()
for Bayesian models to obtain posterior distributions of R-squared.
Changes to functions
r2_bayes()
works with Bayesian models fromBayesFactor
( #143 ).model_performance()
works with Bayesian models fromBayesFactor
( #150 ).model_performance()
now also includes the residual standard deviation.Improved formatting for Bayes factors in
compare_performance()
.compare_performance()
withrank = TRUE
doesn’t use theBF
values whenBIC
are present, to prevent “double-dipping” of the BIC values (#144).The
method
argument incheck_homogeneity()
gains a"levene"
option, to use Levene’s Test for homogeneity.
Bug fixes
- Fix bug in
compare_performance()
when...
arguments were function calls to regression objects, instead of direct function calls.
performance 0.5.0
CRAN release: 2020-09-12
General
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 viaas.numeric()
.
New functions
-
pp_check()
to compute posterior predictive checks for frequentist models.
Bug fixes
Fixed issue with incorrect labeling of groups from
icc()
whenby_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()
forMASS::glm.nb()
.Fixed CRAN check issues.
performance 0.4.8
CRAN release: 2020-07-27
Changes to functions
-
icc()
now also computes a “classical” ICC forbrmsfit
models. The former way of calculating an “ICC” forbrmsfit
models is now available as new function calledvariance_decomposition()
.
Bug fixes
Fix issue with new version of bigutilsr for
check_outliers()
.Fix issue with model order in
performance_lrt()
.
performance 0.4.7
CRAN release: 2020-06-14
Changes to functions
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 aneffects
-argument for mixed models, to check random effects for normality.
Bug fixes
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.
performance 0.4.6
CRAN release: 2020-05-03
General
Minor revisions to
model_performance()
to meet changes in mlogit package.Support for
bayesx
models.
Changes to functions
icc()
gains aby_group
argument, to compute ICCs per different group factors in mixed models with multiple levels or cross-classified design.r2_nakagawa()
gains aby_group
argument, to compute explained variance at different levels (following the variance-reduction approach by Hox 2010).performance_lrt()
now works on lavaan objects.
Bug fixes
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.
performance 0.4.5
CRAN release: 2020-03-28
General
-
model_performance()
andr2()
now support rma-objects from package metafor, mlm and bife models.
Changes to functions
compare_performance()
gets abayesfactor
argument, to include or exclude the Bayes factor for model comparisons in the output.Added
r2.aov()
.
Bug fixes
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.