Function reference • performance

Comprehensive Summaries
`check_model()`	Visual check of model assumptions
`compare_performance()`	Compare performance of different models
`model_performance()` `performance()`	Model Performance
`model_performance(<lm>)`	Performance of Regression Models
`model_performance(<merMod>)`	Performance of Mixed Models
`model_performance(<stanreg>)`	Performance of Bayesian Models
`model_performance(<lavaan>)`	Performance of lavaan SEM / CFA Models
`model_performance(<rma>)`	Performance of Meta-Analysis Models
Common Indices
`icc()` `variance_decomposition()`	Intraclass Correlation Coefficient (ICC)
`looic()`	LOO-related Indices for Bayesian regressions.
`r2()`	Compute the model's R2
Check Model Assumptions or Properties
`binned_residuals()`	Binned residuals for logistic regression
`check_autocorrelation()`	Check model for independence of residuals.
`check_collinearity()` `multicollinearity()`	Check for multicollinearity of model terms
`check_convergence()`	Convergence test for mixed effects models
`check_distribution()`	Classify the distribution of a model-family using machine learning
`check_heteroscedasticity()`	Check model for (non-)constant error variance
`check_homogeneity()`	Check model for homogeneity of variances
`check_normality()`	Check model for (non-)normality of residuals.
`check_outliers()`	Outliers detection (check for influential observations)
`check_overdispersion()`	Check overdispersion of GL(M)M's
`check_singularity()`	Check mixed models for boundary fits
`check_zeroinflation()`	Check for zero-inflation in count models
`pp_check()` `posterior_predictive_check()`	Posterior predictive checks for frequentist models
Check Model Performance or Quality
`performance_accuracy()`	Accuracy of predictions from model fit
`performance_aicc()` `performance_aic()`	Compute AIC and second order AIC
`performance_hosmer()`	Hosmer-Lemeshow goodness-of-fit test
`performance_logloss()`	Log Loss
`performance_lrt()`	Likelihood-Ratio-Test for Model Comparison
`performance_mse()` `mse()`	Mean Square Error of Linear Models
`performance_pcp()`	Percentage of Correct Predictions
`performance_rmse()` `rmse()`	Root Mean Squared Error
`performance_roc()`	Simple ROC curve
`performance_rse()`	Residual Standard Error for Linear Models
`performance_score()`	Proper Scoring Rules
Check Items and Scales
`check_itemscale()`	Describe Properties of Item Scales
`cronbachs_alpha()`	Cronbach's Alpha for Items or Scales
`item_difficulty()`	Difficulty of Questionnaire Items
`item_intercor()`	Mean Inter-Item-Correlation
`item_reliability()`	Reliability Test for Items or Scales
`item_split_half()`	Split-Half Reliability
Further R2 Functions
`r2_bayes()`	Bayesian R2
`r2_coxsnell()`	Cox & Snell's R2
`r2_efron()`	Efron's R2
`r2_kullback()`	Kullback-Leibler R2
`r2_loo()`	LOO-adjusted R2
`r2_mcfadden()`	McFadden's R2
`r2_mckelvey()`	McKelvey & Zavoinas R2
`r2_nagelkerke()`	Nagelkerke's R2
`r2_nakagawa()`	Nakagawa's R2 for mixed models
`r2_tjur()`	Tjur's R2 - coefficient of determination (D)
`r2_xu()`	Xu' R2 (Omega-squared)
`r2_zeroinflated()`	R2 for models with zero-inflation

Reference

Comprehensive Summaries

Common Indices

Check Model Assumptions or Properties

Check Model Performance or Quality

Check Items and Scales

Further R2 Functions