# Processing of Model Parameters

## Documentation for package ‘parameters’ version 0.8.2

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

## Help Pages

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

## -- B --

bootstrap_model | Model bootstrapping
bootstrap_parameters | Parameters bootstrapping

## -- C --

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.betamfx | Confidence Intervals (CI)
ci.betareg | Confidence Intervals (CI)
ci.clm2 | Confidence Intervals (CI)
ci.default | Confidence Intervals (CI)
ci.DirichletRegModel | Confidence Intervals (CI)
ci.glm | Confidence Intervals (CI)
ci.glmmTMB | Confidence Intervals (CI)
ci.hurdle | Confidence Intervals (CI)
ci.lme | Confidence Intervals (CI)
ci.merMod | Confidence Intervals (CI)
ci.MixMod | Confidence Intervals (CI)
ci.mixor | Confidence Intervals (CI)
ci.poissonmfx | Confidence Intervals (CI)
ci.polr | Confidence Intervals (CI)
ci.zeroinfl | 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_robust | Robust estimation
ci_satterthwaite | Satterthwaite approximation for SEs, CIs and p-values
ci_wald | Wald-test approximation for CIs and p-values
closest_component | Principal Component Analysis (PCA)
cluster_analysis | Compute cluster analysis and return group indices
cluster_discrimination | Compute a linear discriminant analysis on classified cluster groups
convert_data_to_numeric | Convert data to numeric
convert_efa_to_cfa | Conversion between EFA results and CFA structure
convert_efa_to_cfa.fa | Conversion between EFA results and CFA structure

## -- D --

data_partition | Partition data into a test and a training set
data_to_numeric | Convert data to numeric
degrees_of_freedom | Degrees of Freedom (DoF)
degrees_of_freedom.default | Degrees of Freedom (DoF)
demean | Compute group-meaned and de-meaned variables
describe_distribution | Describe a distribution
describe_distribution.data.frame | Describe a distribution
describe_distribution.factor | Describe a distribution
describe_distribution.numeric | Describe a distribution
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

## -- E --

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

## -- F --

factor_analysis | Factor Analysis (FA)
fish | Sample data set
format_algorithm | Model Algorithm formatting
format_model | Model Name formatting
format_order | Order (first, second, ...) formatting
format_parameters | Parameter names formatting

## -- G --

get_scores | Get Scores from Principal Component Analysis (PCA)

## -- K --

kurtosis | Compute Skewness and Kurtosis

## -- M --

model_parameters | Model Parameters
model_parameters.aov | Parameters from ANOVAs
model_parameters.befa | Parameters from PCA/FA
model_parameters.betamfx | Parameters from (General) Linear Models
model_parameters.betareg | Parameters from (General) Linear Models
model_parameters.BFBayesFactor | Parameters from BayesFactor objects
model_parameters.bracl | Parameters from multinomial or cumulative link models
model_parameters.brmsfit | Parameters from Bayesian Models
model_parameters.cgam | Parameters from Generalized Additive (Mixed) Models
model_parameters.clm2 | Parameters from (General) Linear Models
model_parameters.clmm | Parameters from Mixed Models
model_parameters.default | Parameters from (General) Linear Models
model_parameters.DirichletRegModel | Parameters from multinomial or cumulative link models
model_parameters.gam | Parameters from Generalized Additive (Mixed) Models
model_parameters.glht | Parameters from Hypothesis Testing
model_parameters.glm | Parameters from (General) Linear Models
model_parameters.glmmTMB | Parameters from Mixed Models
model_parameters.glmx | Parameters from (General) Linear Models
model_parameters.htest | Parameters from Correlations and t-tests
model_parameters.kmeans | Parameters from Cluster Models (k-means, ...)
model_parameters.lavaan | Parameters from CFA/SEM models
model_parameters.logitor | Parameters from (General) Linear Models
model_parameters.Mclust | Parameters from Mixture Models
model_parameters.merMod | Parameters from Mixed Models
model_parameters.mixor | Parameters from Mixed Models
model_parameters.mlm | Parameters from multinomial or cumulative link models
model_parameters.multinom | Parameters from multinomial or cumulative link models
model_parameters.omega | Parameters from Structural Models (PCA, EFA, ...)
model_parameters.PCA | Parameters from Structural Models (PCA, EFA, ...)
model_parameters.poissonmfx | Parameters from (General) Linear Models
model_parameters.principal | Parameters from Structural Models (PCA, EFA, ...)
model_parameters.rma | Parameters from Meta-Analysis
model_parameters.rqss | Parameters from Generalized Additive (Mixed) Models
model_parameters.stanreg | Parameters from Bayesian Models
model_parameters.zeroinfl | Parameters from Zero-Inflated Models

## -- N --

n_clusters | Number of clusters to extract
n_components | Number of components/factors to retain in PCA/FA
n_factors | Number of components/factors to retain in PCA/FA
n_parameters | Count number of parameters in a model
n_parameters.brmsfit | Count number of parameters in a model
n_parameters.default | Count number of parameters in a model
n_parameters.gam | Count number of parameters in a model
n_parameters.glmmTMB | Count number of parameters in a model
n_parameters.merMod | Count number of parameters in a model
n_parameters.zeroinfl | Count number of parameters in a model

## -- P --

parameters | Model Parameters
parameters_table | Parameter table formatting
parameters_type | Type of model parameters
principal_components | Principal Component Analysis (PCA)
print | Print model parameters
print.parameters_kurtosis | Compute Skewness and Kurtosis
print.parameters_model | Print model parameters
print.parameters_skewness | Compute Skewness and Kurtosis
p_value | p-values
p_value.averaging | p-values
p_value.betamfx | p-values
p_value.clm2 | p-values
p_value.default | p-values
p_value.DirichletRegModel | p-values
p_value.emmGrid | p-values
p_value.gee | p-values
p_value.glmmTMB | p-values
p_value.lmerMod | p-values
p_value.merMod | p-values
p_value.MixMod | p-values
p_value.mixor | p-values
p_value.poissonmfx | p-values
p_value.rlmerMod | 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_robust | Robust estimation
p_value_satterthwaite | Satterthwaite approximation for SEs, CIs and p-values
p_value_wald | Wald-test approximation for CIs and p-values
p_value_wald.merMod | Wald-test approximation for 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
rescale_weights | Rescale design weights for multilevel analysis
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

## -- S --

select_parameters | Automated selection of model parameters
select_parameters.lm | Automated selection of model parameters
select_parameters.merMod | Automated selection of model parameters
select_parameters.stanreg | Automated selection of model parameters
se_betwithin | Between-within approximation for SEs, CIs and p-values
se_kenward | Kenward-Roger approximation for SEs, CIs and p-values
se_ml1 | "m-l-1" 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.glmmTMB | Simulated draws from model coefficients
simulate_parameters | Simulate Model Parameters
simulate_parameters.default | Simulate Model Parameters
simulate_parameters.glmmTMB | Simulate Model Parameters
skewness | Compute Skewness and Kurtosis
smoothness | Quantify the smoothness of a vector
standardize_names | Standardize column names
standardize_names.parameters_model | Standardize column names
standard_error | Standard Errors
standard_error.averaging | Standard Errors
standard_error.betamfx | Standard Errors
standard_error.betareg | Standard Errors
standard_error.clm2 | Standard Errors
standard_error.coxph | Standard Errors
standard_error.default | Standard Errors
standard_error.DirichletRegModel | Standard Errors
standard_error.factor | Standard Errors
standard_error.glmmTMB | Standard Errors
standard_error.merMod | Standard Errors
standard_error.MixMod | Standard Errors
standard_error.mixor | Standard Errors
standard_error.poissonmfx | Standard Errors
standard_error.zeroinfl | Standard Errors
standard_error_robust | Robust estimation