Package: parameters 0.22.0

Daniel Lüdecke

parameters: Processing of Model Parameters

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).

Authors:Daniel Lüdecke [aut, cre], Dominique Makowski [aut], Mattan S. Ben-Shachar [aut], Indrajeet Patil [aut], Søren Højsgaard [aut], Brenton M. Wiernik [aut], Zen J. Lau [ctb], Vincent Arel-Bundock [ctb], Jeffrey Girard [ctb], Christina Maimone [rev], Niels Ohlsen [rev], Douglas Ezra Morrison [ctb], Joseph Luchman [ctb]

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parameters.pdf |parameters.html
parameters/json (API)
NEWS

# Install parameters in R:
install.packages('parameters', repos = c('https://easystats.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/easystats/parameters/issues

Datasets:

On CRAN:

betabootstrapciconfidence-intervalsdata-reductioneasystatsfafeature-extractionfeature-reductionhacktoberfestparameterspcapvaluesregression-modelsrobust-statisticsstandardizestandardized-estimatesstatistical-models

84 exports 412 stars 8.12 score 3 dependencies 56 dependents 65.5k downloads

Last updated 1 days agofrom:d4a3b3cf4b5ed037524ca7425cd5dc0a7fd1047f

Exports:bootstrap_modelbootstrap_parameterscici_betwithinci_kenwardci_ml1ci_satterthwaiteclosest_componentcluster_analysiscluster_centerscluster_discriminationcluster_metacluster_performancecompare_modelscompare_parametersconfidence_curveconsonance_functionconvert_efa_to_cfadegrees_of_freedomdemeandescribe_distributiondisplaydofdof_betwithindof_kenwarddof_ml1dof_satterthwaitedominance_analysisefa_to_cfaequivalence_testfactor_analysisformat_df_adjustformat_orderformat_p_adjustformat_parametersget_scoreskurtosismodel_parametersn_clustersn_clusters_dbscann_clusters_elbown_clusters_gapn_clusters_hclustn_clusters_silhouetten_componentsn_factorsn_parametersp_calibratep_functionp_valuep_value_betwithinp_value_kenwardp_value_ml1p_value_satterthwaiteparametersparameters_typepool_parametersprincipal_componentsprint_htmlprint_mdprint_tablerandom_parametersreduce_datareduce_parametersrescale_weightsreshape_loadingsrotated_datase_kenwardse_satterthwaiteselect_parameterssimulate_modelsimulate_parametersskewnesssort_parametersstandard_errorstandardise_infostandardise_parametersstandardise_posteriorsstandardize_infostandardize_namesstandardize_parametersstandardize_posteriorssupported_modelsvisualisation_recipe

Dependencies:bayestestRdatawizardinsight

Overview of Vignettes

Rendered fromoverview_of_vignettes.Rmdusingknitr::rmarkdownon Jun 20 2024.

Last update: 2023-06-01
Started: 2021-02-16

Readme and manuals

Help Manual

Help pageTopics
Model bootstrappingbootstrap_model bootstrap_model.default bootstrap_model.merMod
Parameters bootstrappingbootstrap_parameters bootstrap_parameters.default
Between-within approximation for SEs, CIs and p-valuesci_betwithin dof_betwithin p_value_betwithin
Kenward-Roger approximation for SEs, CIs and p-valuesci_kenward dof_kenward p_value_kenward se_kenward
"m-l-1" approximation for SEs, CIs and p-valuesci_ml1 dof_ml1 p_value_ml1
Satterthwaite approximation for SEs, CIs and p-valuesci_satterthwaite dof_satterthwaite p_value_satterthwaite se_satterthwaite
Confidence Intervals (CI)ci.default ci.glmmTMB ci.merMod
Cluster Analysiscluster_analysis
Find the cluster centers in your datacluster_centers
Compute a linear discriminant analysis on classified cluster groupscluster_discrimination
Metaclusteringcluster_meta
Performance of clustering modelscluster_performance cluster_performance.dbscan cluster_performance.hclust cluster_performance.kmeans cluster_performance.parameters_clusters
Compare model parameters of multiple modelscompare_models compare_parameters
Conversion between EFA results and CFA structureconvert_efa_to_cfa convert_efa_to_cfa.fa efa_to_cfa
Degrees of Freedom (DoF)degrees_of_freedom degrees_of_freedom.default dof
Print tables in different output formatsdisplay.equivalence_test_lm display.parameters_efa display.parameters_efa_summary display.parameters_model display.parameters_sem print_table
Dominance Analysisdominance_analysis
Equivalence testequivalence_test.ggeffects equivalence_test.lm equivalence_test.merMod
Principal Component Analysis (PCA) and Factor Analysis (FA)closest_component factor_analysis predict.parameters_efa principal_components print.parameters_efa rotated_data sort.parameters_efa
Sample data setfish
Format the name of the degrees-of-freedom adjustment methodsformat_df_adjust
Order (first, second, ...) formattingformat_order
Format the name of the p-value adjustment methodsformat_p_adjust
Parameter names formattingformat_parameters format_parameters.default
Print comparisons of model parametersformat.compare_parameters print.compare_parameters print_html.compare_parameters print_md.compare_parameters
Print model parametersformat.parameters_model print.parameters_model print_html.parameters_model print_md.parameters_model summary.parameters_model
Get Scores from Principal Component Analysis (PCA)get_scores
Model Parametersmodel_parameters parameters
Parameters from ANOVAsmodel_parameters.afex_aov model_parameters.aov
Parameters from Bayesian Exploratory Factor Analysismodel_parameters.befa
Parameters from BayesFactor objectsmodel_parameters.BFBayesFactor
Parameters from Generalized Additive (Mixed) Modelsmodel_parameters.cgam model_parameters.Gam model_parameters.gamm model_parameters.scam
Parameters from Mixed Modelsmodel_parameters.clmm model_parameters.clmm2 model_parameters.cpglmm model_parameters.glmmTMB model_parameters.lme model_parameters.merMod model_parameters.mixed model_parameters.MixMod
Parameters from Cluster Models (k-means, ...)model_parameters.dbscan model_parameters.hclust model_parameters.hkmeans model_parameters.kmeans model_parameters.Mclust model_parameters.pam model_parameters.pvclust
Parameters from (General) Linear Modelsmodel_parameters.censReg model_parameters.default model_parameters.glm model_parameters.ridgelm
Parameters from multinomial or cumulative link modelsmodel_parameters.bifeAPEs model_parameters.bracl model_parameters.clm2 model_parameters.DirichletRegModel model_parameters.mlm
Parameters from Hypothesis Testingmodel_parameters.glht
Parameters from special modelsmodel_parameters.averaging model_parameters.betamfx model_parameters.betaor model_parameters.betareg model_parameters.emm_list model_parameters.glimML model_parameters.glmx model_parameters.marginaleffects model_parameters.metaplus model_parameters.meta_bma model_parameters.meta_random model_parameters.mjoint model_parameters.mvord model_parameters.selection
Parameters from hypothesis testsmodel_parameters.coeftest model_parameters.htest
Parameters from Bayesian Modelsmodel_parameters.brmsfit model_parameters.data.frame model_parameters.draws model_parameters.MCMCglmm model_parameters.stanreg
Parameters from multiply imputed repeated analysesmodel_parameters.mipo model_parameters.mira
Parameters from PCA, FA, CFA, SEMmodel_parameters.lavaan model_parameters.PCA model_parameters.principal
Parameters from Meta-Analysismodel_parameters.rma
Parameters from robust statistical objects in 'WRS2'model_parameters.t1way
Parameters from Zero-Inflated Modelsmodel_parameters.mhurdle model_parameters.zcpglm
Find number of clusters in your datan_clusters n_clusters_dbscan n_clusters_elbow n_clusters_gap n_clusters_hclust n_clusters_silhouette
Number of components/factors to retain in PCA/FAn_components n_factors
Calculate calibrated p-values.p_calibrate p_calibrate.default
p-value or consonance functionconfidence_curve consonance_function p_function
p-valuesp_value p_value.default p_value.emmGrid
p-values for Bayesian Modelsp_value.BFBayesFactor
p-values for Models with Special Componentsp_value.averaging p_value.betareg p_value.cgam p_value.clm2 p_value.DirichletRegModel
p-values for Marginal Effects Modelsp_value.betamfx p_value.betaor p_value.poissonmfx
p-values for Models with Zero-Inflationp_value.zcpglm p_value.zeroinfl
Type of model parametersparameters_type
Pool Model Parameterspool_parameters
Predict method for parameters_clusters objectspredict.parameters_clusters
Sample data setqol_cancer
Summary information from random effectsrandom_parameters
Dimensionality reduction (DR) / Features Reductionreduce_data reduce_parameters
Reshape loadings between wide/long formatsreshape_loadings reshape_loadings.data.frame reshape_loadings.parameters_efa
Automated selection of model parametersselect_parameters select_parameters.lm select_parameters.merMod
Simulated draws from model coefficientssimulate_model simulate_model.glmmTMB
Simulate Model Parameterssimulate_parameters simulate_parameters.default simulate_parameters.glmmTMB
Sort parameters by coefficient valuessort_parameters sort_parameters.default
Standard Errorsstandard_error standard_error.default standard_error.factor standard_error.glmmTMB standard_error.merMod
Get Standardization Informationstandardise_info standardize_info standardize_info.default
Parameters standardizationstandardise_parameters standardise_posteriors standardize_parameters standardize_posteriors