Comprehensive Model Parameters

model_parameters() parameters()

Model Parameters

model_parameters(<aov>)

Parameters from ANOVAs

model_parameters(<befa>)

Parameters from PCA/FA

model_parameters(<default>) model_parameters(<betareg>) model_parameters(<clm2>) model_parameters(<glmx>)

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>)

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(<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

print(<parameters_model>)

Print model parameters

Standard Errors, Confidence Intervals 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(<betareg>) ci(<clm2>) ci(<lme>)

Confidence Intervals (CI)

p_value()

p-values

Robust Estimation of SEs, CIs and p-values

standard_error_robust() p_value_robust() ci_robust()

Robust estimation

DoF-approximated SEs, CIs and p-values

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

Other Model Parameters

degrees_of_freedom() dof()

Degrees of Freedom (DoF)

reexports

Objects exported from other packages

equivalence_test(<lm>) equivalence_test(<merMod>)

Equivalence test

n_parameters()

Count number of parameters in a model

random_parameters()

Summary information from random effects

Parameters Engineering

bootstrap_model()

Model bootstrapping

bootstrap_parameters()

Parameters bootstrapping

simulate_model()

Simulated draws from model coefficients

simulate_parameters()

Simulate Model Parameters

Variable Preparation/Centering

check_heterogeneity() demean()

Compute group-meaned and de-meaned variables

rescale_weights()

Rescale design weights for multilevel analysis

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

Data Reduction: 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

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

Miscellaneous

data_partition()

Partition data into a test and a training set

reshape_loadings()

Reshape loadings between wide/long formats

convert_data_to_numeric() data_to_numeric()

Convert data to numeric

Table and Value Formatting

format_algorithm()

Model Algorithm formatting

format_bf()

Bayes Factor formatting

format_model()

Model Name formatting

format_number()

Convert number to words

format_order()

Order (first, second, ...) formatting

format_p()

p-values formatting

format_parameters()

Parameter names formatting

format_pd()

Probability of direction (pd) formatting

format_rope()

Percentage in ROPE formatting

parameters_table()

Parameter table formatting

parameters_type()

Type of model parameters

standardize_names()

Standardize column names