# Assessment of Regression Models Performance

## Documentation for package ‘performance’ version 0.9.0

- DESCRIPTION file.

## Help Pages

B C D I L M P R T V

## -- B --

binned_residuals | Binned residuals for binomial logistic regression

## -- C --

check_autocorrelation | Check model for independence of residuals.
check_autocorrelation.default | Check model for independence of residuals.
check_collinearity | Check for multicollinearity of model terms
check_collinearity.default | Check for multicollinearity of model terms
check_collinearity.glmmTMB | Check for multicollinearity of model terms
check_concurvity | 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_heterogeneity_bias | Check model predictor for heterogeneity bias
check_heteroscedasticity | Check model for (non-)constant error variance
check_heteroskedasticity | Check model for (non-)constant error variance
check_homogeneity | Check model for homogeneity of variances
check_homogeneity.afex_aov | Check model for homogeneity of variances
check_itemscale | Describe Properties of Item Scales
check_model | Visual check of model assumptions
check_model.default | Visual check of model assumptions
check_multimodal | Check if a distribution is unimodal or multimodal
check_normality | Check model for (non-)normality of residuals.
check_normality.merMod | Check model for (non-)normality of residuals.
check_outliers | Outliers detection (check for influential observations)
check_outliers.data.frame | Outliers detection (check for influential observations)
check_outliers.default | Outliers detection (check for influential observations)
check_outliers.numeric | Outliers detection (check for influential observations)
check_overdispersion | Check overdispersion of GL(M)M's
check_posterior_predictions | Posterior predictive checks
check_predictions | Posterior predictive checks
check_singularity | Check mixed models for boundary fits
check_sphericity | Check model for violation of sphericity
check_zeroinflation | Check for zero-inflation in count models
classify_distribution | Classify the distribution of a model-family using machine learning
compare_performance | Compare performance of different models
cronbachs_alpha | Cronbach's Alpha for Items or Scales

## -- D --

display.performance_model | Print tables in different output formats

## -- I --

icc | Intraclass Correlation Coefficient (ICC)
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

## -- L --

looic | LOO-related Indices for Bayesian regressions.

## -- M --

mae | Mean Absolute Error of Models
model_performance | Model Performance
model_performance.BFBayesFactor | Performance of Bayesian Models
model_performance.ivreg | Performance of instrumental variable regression models
model_performance.kmeans | Model summary for k-means clustering
model_performance.lavaan | Performance of lavaan SEM / CFA Models
model_performance.lm | Performance of Regression Models
model_performance.merMod | Performance of Mixed Models
model_performance.rma | Performance of Meta-Analysis Models
model_performance.stanreg | Performance of Bayesian Models
mse | Mean Square Error of Linear Models
multicollinearity | Check for multicollinearity of model terms

## -- P --

performance | Model Performance
performance_accuracy | Accuracy of predictions from model fit
performance_aic | Compute the AIC or second-order AIC
performance_aic.default | Compute the AIC or second-order AIC
performance_aicc | Compute the AIC or second-order AIC
performance_hosmer | Hosmer-Lemeshow goodness-of-fit test
performance_logloss | Log Loss
performance_lrt | Test if models are different
performance_mae | Mean Absolute Error of Models
performance_mse | Mean Square Error of Linear Models
performance_pcp | Percentage of Correct Predictions
performance_rmse | Root Mean Squared Error
performance_roc | Simple ROC curve
performance_rse | Residual Standard Error for Linear Models
performance_score | Proper Scoring Rules
posterior_predictive_check | Posterior predictive checks
print_md.performance_model | Print tables in different output formats

## -- R --

r2 | Compute the model's R2
r2.default | Compute the model's R2
r2.merMod | Compute the model's R2
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_loo_posterior | LOO-adjusted R2
r2_loo_posterior.brmsfit | LOO-adjusted R2
r2_loo_posterior.stanreg | 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_posterior | Bayesian R2
r2_posterior.BFBayesFactor | Bayesian R2
r2_posterior.brmsfit | Bayesian R2
r2_posterior.stanreg | Bayesian R2
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
rmse | Root Mean Squared Error

## -- T --

test_bf | Test if models are different
test_bf.default | Test if models are different
test_likelihoodratio | Test if models are different
test_lrt | Test if models are different
test_performance | Test if models are different
test_vuong | Test if models are different
test_wald | Test if models are different

## -- V --

variance_decomposition | Intraclass Correlation Coefficient (ICC)