Package index
model_performance()performance()- Model Performance
model_performance(<fa>)- Performance of FA / PCA 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>)model_performance(<BFBayesFactor>)- Performance of Bayesian Models
binned_residuals()- Binned residuals for binomial logistic regression
check_autocorrelation()- Check model for independence of residuals.
check_clusterstructure()- Check suitability of data for clustering
check_collinearity()multicollinearity()check_concurvity()- Check for multicollinearity of model terms
check_convergence()- Convergence test for mixed effects models
check_dag()as.dag()- Check correct model adjustment for identifying causal effects
check_distribution()- Classify the distribution of a model-family using machine learning
check_factorstructure()check_kmo()check_sphericity_bartlett()- Check suitability of data for Factor Analysis (FA) with Bartlett's Test of Sphericity and KMO
check_group_variation()summary(<check_group_variation>)- Check variables for within- and/or between-group variation
check_heterogeneity_bias()- Check model predictor for heterogeneity bias(Deprecated)
check_heteroscedasticity()check_heteroskedasticity()- Check model for (non-)constant error variance
check_homogeneity()- Check model for homogeneity of variances
check_itemscale()- Describe Properties of Item Scales
check_model()- 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_outliers()- Outliers detection (check for influential observations)
check_overdispersion()- Check overdispersion (and underdispersion) of GL(M)M's
check_predictions()- Posterior predictive checks
check_residuals()- Check distribution of simulated quantile residuals
check_singularity()- Check mixed models for boundary fits
check_sphericity()- Check model for violation of sphericity
check_symmetry()- Check distribution symmetry
check_zeroinflation()- Check for zero-inflation in count models
simulate_residuals()residuals(<performance_simres>)- Simulate randomized quantile residuals from a model
performance_accuracy()- Accuracy of predictions from model fit
performance_aicc()performance_aic()- Compute the AIC or second-order AIC
performance_cv()- Cross-validated model performance
performance_hosmer()- Hosmer-Lemeshow goodness-of-fit test
performance_logloss()- Log Loss
performance_mae()mae()- Mean Absolute Error of Models
performance_mse()mse()- Mean Square Error of Linear Models
performance_pcp()- Percentage of Correct Predictions
performance_reliability()performance_dvour()- Random Effects Reliability
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
icc()variance_decomposition()- Intraclass Correlation Coefficient (ICC)
looic()- LOO-related Indices for Bayesian regressions.
check_itemscale()- Describe Properties of Item Scales
cronbachs_alpha()item_alpha()- Cronbach's Alpha for Items or Scales
item_difficulty()- Difficulty of Questionnaire Items
item_discrimination()item_totalcor()- Discrimination and Item-Total Correlation of Questionnaire Items
item_intercor()- Mean Inter-Item-Correlation
item_omega()- McDonald's Omega for Items or Scales
item_reliability()- Reliability Test for Items or Scales
item_split_half()- Split-Half Reliability
compare_performance()- Compare performance of different models
test_bf()test_likelihoodratio()test_lrt()test_performance()test_vuong()test_wald()- Test if models are different
r2()- Compute the model's R2
r2_bayes()r2_posterior()- Bayesian R2
r2_coxsnell()- Cox & Snell's R2
r2_efron()- Efron's R2
r2_ferrari()- Ferrari's and Cribari-Neto's R2
r2_kullback()- Kullback-Leibler R2
r2_loo()r2_loo_posterior()- LOO-adjusted R2
r2_mcfadden()- McFadden's R2
r2_mckelvey()- McKelvey & Zavoinas R2
r2_mlm()- Multivariate 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
display(<performance_model>)print(<performance_model>)print_md(<performance_model>)print_md(<compare_performance>)- Print tables in different output formats
reexportsdisplayprint_mdprint_html- Objects exported from other packages
classify_distribution- Classify the distribution of a model-family using machine learning