performance 0.5.0 2020-09-12

General

New functions

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

Bug fixes

performance 0.4.8 2020-07-27

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

performance 0.4.7 2020-06-14

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

performance 0.4.6 2020-05-03

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 2020-03-28

General

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

performance 0.4.4 2020-02-10

General

  • Removed logLik.felm(), because this method is now implemented in the lfe package.
  • Support for DirichletRegModel models.

New functions

Bug fixes

performance 0.4.3 2020-01-22

General

  • Support for mixor, cpglm and cpglmm models.

New functions

  • 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.

Bug fixes

  • Fix issues with CRAN checks.

Changes to functions

performance 0.4.2 2019-12-11

General

Changes to functions

Minor changes

Bug fixes

performance 0.4.0 2019-10-21

General

Deprecated and Defunct

Changes to functions

Bug fixes

  • 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.

performance 0.3.0 2019-08-05

General

Breaking changes

  • 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.

Changes to functions

  • 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.

New check-functions

Bug fixes

  • 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.

performance 0.2.0 2019-06-04

General

  • 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.

New performance-functions

New check-functions

New indices-functions

  • 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.

Breaking changes

  • 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.

Changes to functions

  • 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.

Bug fixes