# performance 0.10.2

## General

* Revised usage of `insight::get_data()` to meet forthcoming changes in the
  _insight_ package.

## Changes to functions

* `check_collinearity()` now accepts `NULL` for the `ci` argument.

## Bug fixes

* 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.

# performance 0.10.1

## General

* Minor improvements to the documentation.

## Changes to functions

* `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.

## Bug fixes

* `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()`.

# performance 0.10.0

## Breaking Change

* The minimum needed R version has been bumped to `3.6`.

* The alias `performance_lrt()` was removed. Use `test_lrt()` resp.
  `test_likelihoodratio()`.

## New functions

* Following functions were moved from package *parameters* to *performance*:
  `check_sphericity_bartlett()`, `check_kmo()`, `check_factorstructure()` and
  `check_clusterstructure()`.

## Changes to functions

* `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.
  
## 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 from `parameters::principal_component()`.

# performance 0.9.2

## General

* `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`.

## Changes to functions

* `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.

## Bug Fixes

* Fixes wrong column names in `model_performance()` output for `kmeans` objects
  (#453)

# performance 0.9.1

## Breaking

* The formerly "conditional" ICC in `icc()` is now named "unadjusted" ICC.

## New functions

* `performance_cv()` for cross-validated model performance.

## Support for new models

* Added support for models from package *estimator*.

## Changes to functions

* `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"`).

## 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 *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.

# performance 0.9.0

## New functions

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

## Changes to functions

### Check functions

* `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 functions

* `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.

### Model performance 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.

### Plotting and printing

* 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.

## Bug fixes

* `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`.

# performance 0.8.0

## Breaking Changes

* 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.

## General

* 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()`.

## New functions

* `check_multimodal()` and `check_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 the `ci`
  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

## Changes to functions

* `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 0.7.2

## 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

## 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()` 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 :-)

## 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 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()`.

### Other functions

* 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`.

## 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 when
  `method = "boot"`.

* `cronbachs_alpha()` did not work for `matrix`-objects, as stated in the docs.
  It now does.

# performance 0.7.0

## General

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

## Breaking Changes

* `compare_performance()` doesn't return the models' Bayes Factors, now returned
  by `test_performance()` and `test_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 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.

## Changes to functions

### `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`.

### 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()` 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.

# performance 0.6.1

## General

* `check_collinearity()` gains a `verbose` argument, to toggle warnings and
  messages.

## Bug fixes

* Fixed examples, now using suggested packages only conditionally.

# performance 0.6.0

## General

* `model_performance()` now supports `margins`, `gamlss`, `stanmvreg` and
  `semLme`.

## 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 for `display(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()` 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.

## Bug fixes

* 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.

# performance 0.5.1

## Breaking changes

* 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`.

## New functions
* `r2_posterior()` for Bayesian models to obtain posterior distributions of
  R-squared.

## Changes to functions

* `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.

## Bug fixes

* Fix bug in `compare_performance()` when `...` arguments were function calls to
  regression objects, instead of direct function calls.

# performance 0.5.0

## General

* `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()`.

## New functions

* `pp_check()` to compute posterior predictive checks for frequentist models.

## Bug fixes

* 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.

# performance 0.4.8

## General

* Removed suggested packages that have been removed from CRAN.

## Changes to functions

* `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()`.

## Bug fixes

* Fix issue with new version of *bigutilsr* for `check_outliers()`.

* Fix issue with model order in `performance_lrt()`.

# performance 0.4.7

## General

* Support for models from package *mfx*.

## 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 an `effects`-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

## General

* Minor revisions to `model_performance()` to meet changes in *mlogit* package.

* Support for `bayesx` models.

## Changes to functions

* `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.

## 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

## General

* `model_performance()` and `r2()` now support *rma*-objects from package
  *metafor*, *mlm* and *bife* models.

## Changes to functions

* `compare_performance()` gets a `bayesfactor` 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.

