Processing of Model Parameters
Parameter names formatting
Practical Significance (ps)
Reshape loadings between wide/long formats
Automated selection of model parameters
Simulated draws from model coefficients
Simulate Model Parameters
Sort parameters by coefficient values
Standard Errors
Get Standardization Information
Parameters standardization
Parameters from PCA, FA, CFA, SEM
p-value or consonance function
Metaclustering
Performance of clustering models
Compare model parameters of multiple models
Format the name of the degrees-of-freedom adjustment methods
Order (first, second, ...) formatting
Format the name of the p-value adjustment methods
Model bootstrapping
Parameters bootstrapping
Confidence Intervals (CI)
Cluster Analysis
Find the cluster centers in your data
Compute a linear discriminant analysis on classified cluster groups
Conversion between EFA results and CFA structure
Degrees of Freedom (DoF)
Print tables in different output formats
Dominance Analysis
help-functions
Safe transformation from factor/character to numeric
for models with zero-inflation component, return required component of...
Bartlett, Anderson and Lawley Procedures
Bentler and Yuan's Procedure
Cattell-Nelson-Gorsuch CNG Indices
Multiple Regression Procedure
Non Graphical Cattell's Scree Test
Standard Error Scree and Coefficient of Determination Procedures
Equivalence test
Extract factor scores from Factor Analysis (EFA) or Omega
Parameters from multiply imputed repeated analyses
Parameters from multinomial or cumulative link models
Get Scores from Principal Component or Factor Analysis (PCA/FA)
Parameters from ANOVAs
Parameters from Bayesian Exploratory Factor Analysis
Parameters from BayesFactor objects
Parameters from Bayesian Models
Parameters from Generalized Additive (Mixed) Models
Bayesian Model Comparison
Parameters from (General) Linear Models
Parameters from Hypothesis Testing
Parameters from special models
Parameters from Mixed Models
Parameters from Cluster Models (k-means, ...)
Parameters from hypothesis tests
Model Parameters
Parameters from Meta-Analysis
Parameters from robust statistical objects in WRS2
Parameters from Zero-Inflated Models
Find number of clusters in your data
Number of components/factors to retain in PCA/FA
Calculate calibrated p-values.
Probability of Direction (pd)
Between-within approximation for SEs, CIs and p-values
Kenward-Roger approximation for SEs, CIs and p-values
"m-l-1" approximation for SEs, CIs and p-values
Satterthwaite approximation for SEs, CIs and p-values
p-values
Type of model parameters
Global options from the parameters package
parameters: Extracting, Computing and Exploring the Parameters of Stat...
Pool Model Parameters
Predict method for parameters_clusters objects
Principal Component Analysis (PCA) and Factor Analysis (FA)
Print comparisons of model parameters
Print model parameters
Summary information from random effects
Dimensionality reduction (DR) / Features Reduction
Objects exported from other packages
Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see list of supported models using the function 'insight::supported_models()'), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).