Function reference • parameters

Comprehensive Model Parameters
`model_parameters()` `parameters()`	Model Parameters
`model_parameters(<aov>)`	Parameters from ANOVAs
`model_parameters(<befa>)`	Parameters from PCA/FA
`model_parameters(<logitor>)` `model_parameters(<poissonmfx>)` `model_parameters(<betamfx>)` `model_parameters(<default>)` `model_parameters(<glm>)`	Parameters from (General) Linear Models
`model_parameters(<zeroinfl>)`	Parameters from Zero-Inflated Models
`model_parameters(<gam>)` `model_parameters(<rqss>)` `model_parameters(<cgam>)`	Parameters from Generalized Additive (Mixed) Models
`model_parameters(<mlm>)` `model_parameters(<multinom>)` `model_parameters(<bracl>)` `model_parameters(<DirichletRegModel>)` `model_parameters(<clm2>)`	Parameters from multinomial or cumulative link models
`model_parameters(<merMod>)` `model_parameters(<glmmTMB>)` `model_parameters(<mixor>)` `model_parameters(<clmm>)`	Parameters from Mixed Models
`model_parameters(<lavaan>)`	Parameters from CFA/SEM models
`model_parameters(<kmeans>)`	Parameters from Cluster Models (k-means, ...)
`model_parameters(<Mclust>)`	Parameters from Mixture Models
`model_parameters(<mira>)`	Parameters from multiply imputed repeated analyses
`model_parameters(<PCA>)` `model_parameters(<principal>)` `model_parameters(<omega>)`	Parameters from Structural Models (PCA, EFA, ...)
`model_parameters(<stanreg>)` `model_parameters(<brmsfit>)`	Parameters from Bayesian Models
`model_parameters(<BFBayesFactor>)`	Parameters from BayesFactor objects
`model_parameters(<rma>)`	Parameters from Meta-Analysis
`model_parameters(<htest>)`	Parameters from Correlations and t-tests
`model_parameters(<glht>)`	Parameters from Hypothesis Testing
`model_parameters(<averaging>)` `model_parameters(<betareg>)` `model_parameters(<glmx>)`	Parameters from special models
`random_parameters()`	Summary information from random effects
`print(<parameters_model>)`	Print model parameters
Standard Errors, Confidence Intervals, Degrees of Freesom and p-values
`standard_error()`	Standard Errors
`ci(<merMod>)` `ci(<default>)` `ci(<glm>)` `ci(<polr>)` `ci(<mixor>)` `ci(<DirichletRegModel>)` `ci(<glmmTMB>)` `ci(<zeroinfl>)` `ci(<hurdle>)` `ci(<MixMod>)` `ci(<poissonmfx>)` `ci(<betamfx>)` `ci(<betareg>)` `ci(<clm2>)` `ci(<lme>)`	Confidence Intervals (CI)
`p_value()`	p-values
`degrees_of_freedom()` `dof()`	Degrees of Freedom (DoF)
`n_parameters()`	Count number of parameters in a model
Robust Estimation Methods
`standard_error_robust()` `p_value_robust()` `ci_robust()`	Robust estimation
Approximation Methods
`ci_wald()` `p_value_wald()`	Wald-test approximation for CIs and p-values
`ci_kenward()` `dof_kenward()` `p_value_kenward()` `se_kenward()`	Kenward-Roger approximation for SEs, CIs and p-values
`ci_satterthwaite()` `dof_satterthwaite()` `p_value_satterthwaite()` `se_satterthwaite()`	Satterthwaite approximation for SEs, CIs and p-values
`ci_betwithin()` `dof_betwithin()` `p_value_betwithin()` `se_betwithin()`	Between-within approximation for SEs, CIs and p-values
`ci_ml1()` `dof_ml1()` `p_value_ml1()` `se_ml1()`	"m-l-1" approximation for SEs, CIs and p-values
Effect Existence and Significance
`reexports`	Objects exported from other packages
`equivalence_test(<lm>)` `equivalence_test(<merMod>)`	Equivalence test
Parameter Sampling
`bootstrap_model()`	Model bootstrapping
`bootstrap_parameters()`	Parameters bootstrapping
`simulate_model()`	Simulated draws from model coefficients
`simulate_parameters()`	Simulate Model Parameters
Variable Preparation
`check_heterogeneity()` `demean()`	Compute group-meaned and de-meaned variables
`rescale_weights()`	Rescale design weights for multilevel analysis
`data_partition()`	Partition data into a test and a training set
`convert_data_to_numeric()` `data_to_numeric()`	Convert data to numeric
Feature Reduction
`reduce_parameters()` `reduce_data()`	Dimensionality reduction (DR) / Features Reduction
`select_parameters()`	Automated selection of model parameters
Data Reduction
Cluster Analysis
`check_clusterstructure()`	Check suitability of data for clustering
`cluster_analysis()`	Compute cluster analysis and return group indices
`cluster_discrimination()`	Compute a linear discriminant analysis on classified cluster groups
`n_clusters()`	Number of clusters to extract
Factors and Principal Components
`check_factorstructure()`	Check suitability of data for Factor Analysis (FA)
`check_kmo()`	Kaiser, Meyer, Olkin (KMO) Measure of Sampling Adequacy (MSA) for Factor Analysis
`check_sphericity()`	Bartlett's Test of Sphericity
`convert_efa_to_cfa()` `efa_to_cfa()`	Conversion between EFA results and CFA structure
`factor_analysis()`	Factor Analysis (FA)
`get_scores()`	Get Scores from Principal Component Analysis (PCA)
`n_factors()` `n_components()`	Number of components/factors to retain in PCA/FA
`principal_components()` `closest_component()`	Principal Component Analysis (PCA)
`reduce_parameters()` `reduce_data()`	Dimensionality reduction (DR) / Features Reduction
`reshape_loadings()`	Reshape loadings between wide/long formats
Data Properties
`describe_distribution()`	Describe a distribution
`check_multimodal()`	Check if a distribution is unimodal or multimodal
`skewness()` `kurtosis()` `print(<parameters_kurtosis>)` `print(<parameters_skewness>)`	Compute Skewness and Kurtosis
`smoothness()`	Quantify the smoothness of a vector
Table and Value Formatting
`reexports`	Objects exported from other packages
`format_order()`	Order (first, second, ...) formatting
`format_parameters()`	Parameter names formatting
`parameters_table()`	Parameter table formatting
`parameters_type()`	Type of model parameters
`standardize_names()`	Standardize column names
Example Data Sets
`qol_cancer`	Sample data set
`fish`	Sample data set

Reference

Comprehensive Model Parameters

Standard Errors, Confidence Intervals, Degrees of Freesom and p-values

Robust Estimation Methods

Approximation Methods

Effect Existence and Significance

Parameter Sampling

Variable Preparation

Feature Reduction

Data Reduction

Cluster Analysis

Factors and Principal Components

Data Properties

Table and Value Formatting

Example Data Sets