bootstrap_model         Model bootstrapping
bootstrap_parameters    Parameters bootstrapping
center                  Centering (Grand-Mean Centering)
check_clusterstructure
                        Check suitability of data for clustering
check_factorstructure   Check suitability of data for Factor Analysis
                        (FA)
check_heterogeneity     Compute group-meaned and de-meaned variables
check_kmo               Kaiser, Meyer, Olkin (KMO) Measure of Sampling
                        Adequacy (MSA) for Factor Analysis
check_multimodal        Check if a distribution is unimodal or
                        multimodal
check_sphericity        Bartlett's Test of Sphericity
ci.default              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
ci_wald                 Wald-test approximation for CIs and p-values
cluster_analysis        Compute cluster analysis and return group
                        indices
cluster_discrimination
                        Compute a linear discriminant analysis on
                        classified cluster groups
compare_parameters      Compare model parameters of multiple models
convert_data_to_numeric
                        Convert data to numeric
convert_efa_to_cfa      Conversion between EFA results and CFA
                        structure
data_partition          Partition data into a test and a training set
degrees_of_freedom      Degrees of Freedom (DoF)
describe_distribution   Describe a distribution
display.parameters_model
                        Print tables in different output formats
equivalence_test.lm     Equivalence test
factor_analysis         Factor Analysis (FA)
fish                    Sample data set
format_order            Order (first, second, ...) formatting
format_p_adjust         Format the name of the p-value adjustment
                        methods
format_parameters       Parameter names formatting
get_scores              Get Scores from Principal Component Analysis
                        (PCA)
model_parameters        Model Parameters
model_parameters.BFBayesFactor
                        Parameters from BayesFactor objects
model_parameters.DirichletRegModel
                        Parameters from multinomial or cumulative link
                        models
model_parameters.Mclust
                        Parameters from Mixture Models
model_parameters.PCA    Parameters from Structural Models (PCA, EFA,
                        ...)
model_parameters.PMCMR
                        Parameters from Hypothesis Testing
model_parameters.aov    Parameters from ANOVAs
model_parameters.averaging
                        Parameters from special models
model_parameters.befa   Parameters from PCA/FA
model_parameters.cgam   Parameters from Generalized Additive (Mixed)
                        Models
model_parameters.cpglmm
                        Parameters from Mixed Models
model_parameters.data.frame
                        Parameters from Bayesian Models
model_parameters.default
                        Parameters from (General) Linear Models
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.mira   Parameters from multiply imputed repeated
                        analyses
model_parameters.rma    Parameters from Meta-Analysis
model_parameters.t1way
                        Parameters from robust statistical objects in
                        'WRS2'
model_parameters.zcpglm
                        Parameters from Zero-Inflated Models
n_clusters              Number of clusters to extract
n_factors               Number of components/factors to retain in
                        PCA/FA
p_value                 p-values
p_value.BFBayesFactor   p-values for Bayesian Models
p_value.DirichletRegModel
                        p-values for Models with Special Components
p_value.cpglmm          p-values for Mixed Models
p_value.poissonmfx      p-values for Marginal Effects Models
p_value.zcpglm          p-values for Models with Zero-Inflation
parameters_type         Type of model parameters
pool_parameters         Pool Model Parameters
principal_components    Principal Component Analysis (PCA)
print.parameters_model
                        Print model parameters
qol_cancer              Sample data set
random_parameters       Summary information from random effects
reduce_parameters       Dimensionality reduction (DR) / Features
                        Reduction
rescale_weights         Rescale design weights for multilevel analysis
reshape_loadings        Reshape loadings between wide/long formats
select_parameters       Automated selection of model parameters
simulate_model          Simulated draws from model coefficients
simulate_parameters.glmmTMB
                        Simulate Model Parameters
skewness                Compute Skewness and (Excess) Kurtosis
smoothness              Quantify the smoothness of a vector
standard_error          Standard Errors
standard_error_robust   Robust estimation
