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>)` `model_performance(<BFBayesFactor>)`	Performance of Bayesian Models
`model_performance(<lavaan>)`	Performance of lavaan SEM / CFA Models
`model_performance(<rma>)`	Performance of Meta-Analysis Models
`model_performance(<ivreg>)`	Performance of instrumental variable regression 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_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
Comparing Models
`test_likelihoodratio()` `performance_lrt()` `test_performance()` `test_vuong()` `test_wald()`	Test if Models are Different
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()` `r2_posterior()`	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_somers()`	Somers' Dxy rank correlation for binary outcomes
`r2_tjur()`	Tjur's R2 - coefficient of determination (D)
`r2_xu()`	Xu' R2 (Omega-squared)
`r2_zeroinflated()`	R2 for models with zero-inflation
Table Formatting
`display(<performance_model>)` `print_md(<performance_model>)`	Print tables in different output formats
`reexports`	Objects exported from other packages
Sample Data
`classify_distribution`	Machine learning model trained to classify distributions

Reference

Comprehensive Summaries

Common Indices

Check Model Assumptions or Properties

Check Model Performance or Quality

Comparing Models

Check Items and Scales

Further R2 Functions

Table Formatting

Sample Data