| bootstrap_model | Model bootstrapping |
| bootstrap_model.default | Model bootstrapping |
| bootstrap_model.merMod | Model bootstrapping |
| bootstrap_parameters | Parameters bootstrapping |
| check_clusterstructure | Check suitability of data for clustering |
| check_factorstructure | Check suitability of data for Factor Analysis (FA) |
| check_heterogeneity | Check model predictor for heterogeneity bias |
| check_kmo | Kaiser, Meyer, Olkin (KMO) Measure of Sampling Adequacy (MSA) for Factor Analysis |
| check_sphericity_bartlett | Bartlett's Test of Sphericity |
| ci.default | Confidence Intervals (CI) |
| ci.glmmTMB | Confidence Intervals (CI) |
| ci.merMod | Confidence Intervals (CI) |
| ci_betwithin | Between-within approximation for SEs, CIs and p-values |
| ci_kenward | Kenward-Roger approximation for SEs, CIs and p-values |
| ci_ml1 | "m-l-1" approximation for SEs, CIs and p-values |
| ci_satterthwaite | Satterthwaite approximation for SEs, CIs and p-values |
| closest_component | Principal Component Analysis (PCA) and Factor Analysis (FA) |
| cluster_analysis | Cluster Analysis |
| cluster_centers | Find the cluster centers in your data |
| cluster_discrimination | Compute a linear discriminant analysis on classified cluster groups |
| cluster_meta | Metaclustering |
| cluster_performance | Performance of clustering models |
| cluster_performance.dbscan | Performance of clustering models |
| cluster_performance.hclust | Performance of clustering models |
| cluster_performance.kmeans | Performance of clustering models |
| cluster_performance.parameters_clusters | Performance of clustering models |
| compare_models | Compare model parameters of multiple models |
| compare_parameters | Compare model parameters of multiple models |
| convert_efa_to_cfa | Conversion between EFA results and CFA structure |
| convert_efa_to_cfa.fa | Conversion between EFA results and CFA structure |
| degrees_of_freedom | Degrees of Freedom (DoF) |
| degrees_of_freedom.default | Degrees of Freedom (DoF) |
| display.equivalence_test_lm | Print tables in different output formats |
| display.parameters_efa | Print tables in different output formats |
| display.parameters_efa_summary | Print tables in different output formats |
| display.parameters_model | Print tables in different output formats |
| display.parameters_sem | Print tables in different output formats |
| dof | Degrees of Freedom (DoF) |
| dof_betwithin | Between-within approximation for SEs, CIs and p-values |
| dof_kenward | Kenward-Roger approximation for SEs, CIs and p-values |
| dof_ml1 | "m-l-1" approximation for SEs, CIs and p-values |
| dof_satterthwaite | Satterthwaite approximation for SEs, CIs and p-values |
| efa_to_cfa | Conversion between EFA results and CFA structure |
| equivalence_test.lm | Equivalence test |
| equivalence_test.merMod | Equivalence test |
| factor_analysis | Principal Component Analysis (PCA) and Factor Analysis (FA) |
| fish | Sample data set |
| format.parameters_model | Print tables in different output formats |
| format_df_adjust | Format the name of the degrees-of-freedom adjustment methods |
| format_order | Order (first, second, ...) formatting |
| format_parameters | Parameter names formatting |
| format_parameters.default | Parameter names formatting |
| format_p_adjust | Format the name of the p-value adjustment methods |
| get_scores | Get Scores from Principal Component Analysis (PCA) |
| model_parameters | Model Parameters |
| model_parameters.aov | Parameters from ANOVAs |
| model_parameters.averaging | Parameters from special models |
| model_parameters.befa | Parameters from Bayesian Exploratory Factor Analysis |
| model_parameters.betamfx | Parameters from (General) Linear Models |
| model_parameters.betareg | Parameters from special models |
| model_parameters.BFBayesFactor | Parameters from BayesFactor objects |
| model_parameters.bifeAPEs | Parameters from multinomial or cumulative link models |
| model_parameters.bracl | Parameters from multinomial or cumulative link models |
| model_parameters.brmsfit | Parameters from Bayesian Models |
| model_parameters.cgam | Parameters from Generalized Additive (Mixed) Models |
| model_parameters.clm2 | Parameters from multinomial or cumulative link models |
| model_parameters.clmm | Parameters from Mixed Models |
| model_parameters.cpglmm | Parameters from Mixed Models |
| model_parameters.data.frame | Parameters from Bayesian Models |
| model_parameters.dbscan | Parameters from Cluster Models (k-means, ...) |
| model_parameters.default | Parameters from (General) Linear Models |
| model_parameters.DirichletRegModel | Parameters from multinomial or cumulative link models |
| model_parameters.gam | Parameters from Generalized Additive (Mixed) Models |
| model_parameters.glht | Parameters from Hypothesis Testing |
| model_parameters.glm | Parameters from (General) Linear Models |
| model_parameters.glmmTMB | Parameters from Mixed Models |
| model_parameters.glmx | Parameters from special models |
| model_parameters.hclust | Parameters from Cluster Models (k-means, ...) |
| model_parameters.hkmeans | Parameters from Cluster Models (k-means, ...) |
| model_parameters.htest | Parameters from hypothesis tests |
| model_parameters.kmeans | Parameters from Cluster Models (k-means, ...) |
| model_parameters.lavaan | Parameters from CFA/SEM models |
| model_parameters.logitor | Parameters from (General) Linear Models |
| model_parameters.Mclust | Parameters from Cluster Models (k-means, ...) |
| model_parameters.merMod | Parameters from Mixed Models |
| model_parameters.mira | Parameters from multiply imputed repeated analyses |
| model_parameters.mixor | Parameters from Mixed Models |
| model_parameters.mlm | Parameters from multinomial or cumulative link models |
| model_parameters.omega | Parameters from Structural Models (PCA, EFA, ...) |
| model_parameters.pairwise.htest | Parameters from hypothesis tests |
| model_parameters.pam | Parameters from Cluster Models (k-means, ...) |
| model_parameters.PCA | Parameters from Structural Models (PCA, EFA, ...) |
| model_parameters.PMCMR | Parameters from Hypothesis Testing |
| model_parameters.poissonmfx | Parameters from (General) Linear Models |
| model_parameters.principal | Parameters from Structural Models (PCA, EFA, ...) |
| model_parameters.pvclust | Parameters from Cluster Models (k-means, ...) |
| model_parameters.rma | Parameters from Meta-Analysis |
| model_parameters.rqss | Parameters from Generalized Additive (Mixed) Models |
| model_parameters.stanreg | Parameters from Bayesian Models |
| model_parameters.t1way | Parameters from robust statistical objects in 'WRS2' |
| model_parameters.zcpglm | Parameters from Zero-Inflated Models |
| n_clusters | Find number of clusters in your data |
| n_clusters_dbscan | Find number of clusters in your data |
| n_clusters_elbow | Find number of clusters in your data |
| n_clusters_gap | Find number of clusters in your data |
| n_clusters_hclust | Find number of clusters in your data |
| n_clusters_silhouette | Find number of clusters in your data |
| n_components | Number of components/factors to retain in PCA/FA |
| n_factors | Number of components/factors to retain in PCA/FA |
| parameters | Model Parameters |
| parameters_type | Type of model parameters |
| pool_parameters | Pool Model Parameters |
| predict.parameters_clusters | Predict method for parameters_clusters objects |
| predict.parameters_efa | Principal Component Analysis (PCA) and Factor Analysis (FA) |
| principal_components | Principal Component Analysis (PCA) and Factor Analysis (FA) |
| print.parameters_efa | Principal Component Analysis (PCA) and Factor Analysis (FA) |
| print.parameters_model | Print model parameters |
| print_html.parameters_model | Print tables in different output formats |
| print_md.parameters_model | Print tables in different output formats |
| p_value | p-values |
| p_value.averaging | p-values for Models with Special Components |
| p_value.betamfx | p-values for Marginal Effects Models |
| p_value.betaor | p-values for Marginal Effects Models |
| p_value.betareg | p-values for Models with Special Components |
| p_value.BFBayesFactor | p-values for Bayesian Models |
| p_value.cgam | p-values for Models with Special Components |
| p_value.clm2 | p-values for Models with Special Components |
| p_value.default | p-values |
| p_value.DirichletRegModel | p-values for Models with Special Components |
| p_value.emmGrid | p-values |
| p_value.poissonmfx | p-values for Marginal Effects Models |
| p_value.zcpglm | p-values for Models with Zero-Inflation |
| p_value.zeroinfl | p-values for Models with Zero-Inflation |
| p_value_betwithin | Between-within approximation for SEs, CIs and p-values |
| p_value_kenward | Kenward-Roger approximation for SEs, CIs and p-values |
| p_value_ml1 | "m-l-1" approximation for SEs, CIs and p-values |
| p_value_satterthwaite | Satterthwaite approximation for SEs, CIs and p-values |
| qol_cancer | Sample data set |
| random_parameters | Summary information from random effects |
| reduce_data | Dimensionality reduction (DR) / Features Reduction |
| reduce_parameters | Dimensionality reduction (DR) / Features Reduction |
| reshape_loadings | Reshape loadings between wide/long formats |
| reshape_loadings.data.frame | Reshape loadings between wide/long formats |
| reshape_loadings.parameters_efa | Reshape loadings between wide/long formats |
| rotated_data | Principal Component Analysis (PCA) and Factor Analysis (FA) |
| select_parameters | Automated selection of model parameters |
| select_parameters.lm | Automated selection of model parameters |
| select_parameters.merMod | Automated selection of model parameters |
| select_parameters.stanreg | Automated selection of model parameters |
| se_kenward | Kenward-Roger approximation for SEs, CIs and p-values |
| se_satterthwaite | Satterthwaite approximation for SEs, CIs and p-values |
| simulate_model | Simulated draws from model coefficients |
| simulate_model.glmmTMB | Simulated draws from model coefficients |
| simulate_parameters | Simulate Model Parameters |
| simulate_parameters.default | Simulate Model Parameters |
| simulate_parameters.glmmTMB | Simulate Model Parameters |
| sort.parameters_efa | Principal Component Analysis (PCA) and Factor Analysis (FA) |
| standard_error | Standard Errors |
| standard_error.averaging | Standard Errors |
| standard_error.betamfx | Standard Errors |
| standard_error.betareg | Standard Errors |
| standard_error.clm2 | Standard Errors |
| standard_error.coxph | Standard Errors |
| standard_error.default | Standard Errors |
| standard_error.DirichletRegModel | Standard Errors |
| standard_error.factor | Standard Errors |
| standard_error.glmmTMB | Standard Errors |
| standard_error.merMod | Standard Errors |
| standard_error.MixMod | Standard Errors |
| standard_error.mixor | Standard Errors |
| standard_error.poissonmfx | Standard Errors |
| standard_error.zeroinfl | Standard Errors |
| standard_error_robust | Robust standard errors. Superseded by the vcov* arguments in 'standard_error()' |
| summary.parameters_model | Print model parameters |