# Processing of Model Parameters

## Documentation for package ‘parameters’ version 0.28.3

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

B C D E F G M N P Q R S

## -- B --

bootstrap_model | Model bootstrapping
bootstrap_model.default | Model bootstrapping
bootstrap_parameters | Parameters bootstrapping
bootstrap_parameters.default | Parameters bootstrapping

## -- C --

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
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.hclust | Performance of clustering models
compare_models | Compare model parameters of multiple models
compare_parameters | Compare model parameters of multiple models
confidence_curve | p-value or consonance function
consonance_function | p-value or consonance function
convert_efa_to_cfa | Conversion between EFA results and CFA structure
convert_efa_to_cfa.fa | Conversion between EFA results and CFA structure

## -- D --

degrees_of_freedom | Degrees of Freedom (DoF)
display.parameters_model | 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
dominance_analysis | Dominance Analysis

## -- E --

efa_to_cfa | Conversion between EFA results and CFA structure
equivalence_test.lm | Equivalence test

## -- F --

factor_analysis | Principal Component Analysis (PCA) and Factor Analysis (FA)
factor_analysis.data.frame | Principal Component Analysis (PCA) and Factor Analysis (FA)
factor_analysis.matrix | Principal Component Analysis (PCA) and Factor Analysis (FA)
factor_scores | Extract factor scores from Factor Analysis (EFA) or Omega
fish | Sample data set
format.compare_parameters | Print comparisons of model parameters
format.parameters_model | Print model parameters
format.parameters_p_function | p-value or consonance function
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

## -- G --

get_scores | Get Scores from Principal Component or Factor Analysis (PCA/FA)

## -- M --

model_parameters | Model Parameters
model_parameters.aov | Parameters from ANOVAs
model_parameters.befa | Parameters from Bayesian Exploratory Factor Analysis
model_parameters.BFBayesFactor | Parameters from BayesFactor objects
model_parameters.brmsfit | Parameters from Bayesian Models
model_parameters.cgam | Parameters from Generalized Additive (Mixed) Models
model_parameters.coeftest | Parameters from hypothesis tests
model_parameters.compare.loo | Bayesian Model Comparison
model_parameters.data.frame | Parameters from Bayesian Models
model_parameters.default | Parameters from (General) Linear Models
model_parameters.glht | Parameters from Hypothesis Testing
model_parameters.glimML | Parameters from special models
model_parameters.glmmTMB | Parameters from Mixed Models
model_parameters.hclust | Parameters from Cluster Models (k-means, ...)
model_parameters.htest | Parameters from hypothesis tests
model_parameters.lavaan | Parameters from PCA, FA, CFA, SEM
model_parameters.mira | Parameters from multiply imputed repeated analyses
model_parameters.mlm | Parameters from multinomial or cumulative link models
model_parameters.principal | Parameters from PCA, FA, CFA, SEM
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 --

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

## -- P --

parameters | Model Parameters
parameters-options | Global options from the parameters package
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)
principal_components.data.frame | Principal Component Analysis (PCA) and Factor Analysis (FA)
print.compare_parameters | Print comparisons of model parameters
print.parameters_efa | Principal Component Analysis (PCA) and Factor Analysis (FA)
print.parameters_model | Print model parameters
print.parameters_p_function | p-value or consonance function
print_html.compare_parameters | Print comparisons of model parameters
print_html.parameters_efa | Principal Component Analysis (PCA) and Factor Analysis (FA)
print_html.parameters_model | Print model parameters
print_html.parameters_p_function | p-value or consonance function
print_md.compare_parameters | Print comparisons of model parameters
print_md.parameters_model | Print model parameters
p_calibrate | Calculate calibrated p-values.
p_calibrate.default | Calculate calibrated p-values.
p_direction.lm | Probability of Direction (pd)
p_function | p-value or consonance function
p_significance.lm | Practical Significance (ps)
p_value | p-values
p_value.default | p-values
p_value.emmGrid | p-values
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

## -- Q --

qol_cancer | Sample data set

## -- R --

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)

## -- S --

select_parameters | Automated selection of model parameters
select_parameters.lm | Automated selection of model parameters
select_parameters.merMod | 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.default | Simulated draws from model coefficients
simulate_parameters | Simulate Model Parameters
simulate_parameters.default | Simulate Model Parameters
sort.parameters_efa | Principal Component Analysis (PCA) and Factor Analysis (FA)
sort_parameters | Sort parameters by coefficient values
sort_parameters.default | Sort parameters by coefficient values
standardise_info | Get Standardization Information
standardise_parameters | Parameters standardization
standardise_posteriors | Parameters standardization
standardize_info | Get Standardization Information
standardize_info.default | Get Standardization Information
standardize_parameters | Parameters standardization
standardize_posteriors | Parameters standardization
standard_error | Standard Errors
standard_error.default | Standard Errors
standard_error.factor | Standard Errors
summary.parameters_model | Print model parameters