check_clusterstructure | Check suitability of data for Clustering |
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_multimodal | Check if a distribution is unimodal or multimodal |
check_sphericity | Bartlett's Test of Sphericity |
ci.default | Confidence Interval (CI) |
ci.glm | Confidence Interval (CI) |
ci.glmmTMB | Confidence Interval (CI) |
ci.hurdle | Confidence Interval (CI) |
ci.merMod | Confidence Interval (CI) |
ci.MixMod | Confidence Interval (CI) |
ci.zeroinfl | Confidence Interval (CI) |
ci_robust | Confidence Interval (CI) |
ci_wald | Wald-test approximation for CIs and p-values |
cluster_analysis | Compute cluster analysis and return group indices |
cluster_discrimination | Compute a linear discriminant analysis on classified cluster groups |
cmds | Classical Multidimensional Scaling (cMDS) |
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 |
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) |
demean | Compute group-meaned and de-meaned variables |
describe_distribution | Describe a Distribution |
dof | Degrees of Freedom (DoF) |
dof_kenward | p-values using Kenward-Roger approximation |
DRR | Dimensionality Reduction via Regression (DRR) |
efa_to_cfa | Conversion between EFA results and CFA structure |
equivalence_test.lm | Equivalence test |
factor_analysis | Factor Analysis (FA) |
format_algorithm | Model Algorithm Formatting |
format_bf | Bayes Factor Formatting |
format_ci | Confidence/Credible Interval (CI) 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 | Parameters Names Formatting |
format_pd | Probability of direction (pd) Formatting |
format_rope | Percentage in ROPE Formatting |
ICA | Independent Component Analysis (ICA) |
kurtosis | Compute Skewness and Kurtosis |
model_bootstrap | Model bootstrapping |
model_parameters | Model Parameters |
model_parameters.aov | ANOVAs Parameters |
model_parameters.befa | Format PCA/FA from the psych package |
model_parameters.BFBayesFactor | BayesFactor objects Parameters |
model_parameters.brmsfit | Bayesian Models Parameters |
model_parameters.default | Parameters of (General) Linear Models |
model_parameters.gam | Parameters of Generalized Additive (Mixed) Models |
model_parameters.glmmTMB | Mixed Model Parameters |
model_parameters.htest | Correlations and t-test Parameters |
model_parameters.kmeans | Cluster Models (k-means, ...) |
model_parameters.lavaan | Format CFA/SEM from the lavaan package |
model_parameters.Mclust | Mixture Models Parameters |
model_parameters.merMod | Mixed Model Parameters |
model_parameters.omega | Structural Models (PCA, EFA, ...) |
model_parameters.PCA | Structural Models (PCA, EFA, ...) |
model_parameters.principal | Structural Models (PCA, EFA, ...) |
model_parameters.stanreg | Bayesian Models Parameters |
model_parameters.zeroinfl | Model Parameters for Zero-Inflated Models |
model_simulate | Simulated draws from model coefficients |
model_simulate.glmmTMB | Simulated draws from model coefficients |
n_clusters | Number of Clusters to Extract |
n_factors | Number of Components/Factors to Retain in Factor Analysis |
n_parameters | Count number parameters in a model |
n_parameters.brmsfit | Count number parameters in a model |
n_parameters.default | Count number parameters in a model |
n_parameters.gam | Count number parameters in a model |
n_parameters.glmmTMB | Count number parameters in a model |
n_parameters.merMod | Count number parameters in a model |
n_parameters.zeroinfl | Count number parameters in a model |
parameters | Model Parameters |
parameters_bootstrap | Parameters bootstrapping |
parameters_reduction | Dimensionality reduction (DR) / Features Reduction |
parameters_selection | Parameters Selection |
parameters_selection.lm | Parameters Selection |
parameters_selection.merMod | Parameters Selection |
parameters_selection.stanreg | Parameters Selection |
parameters_simulate | Parameters simulation |
parameters_simulate.default | Parameters simulation |
parameters_table | Parameters Table Formatting |
parameters_type | Type of Model Parameters |
principal_components | Principal Component Analysis (PCA) |
Print model parameters | |
print.parameters_model | Print model parameters |
p_value | p-values |
p_value.glmmTMB | p-values |
p_value.lmerMod | p-values |
p_value.MixMod | p-values |
p_value_kenward | p-values using Kenward-Roger approximation |
p_value_robust | 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 |
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 |
se_kenward | p-values using Kenward-Roger approximation |
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 | Extract standard errors |
standard_error.default | Extract standard errors |
standard_error.factor | Extract standard errors |
standard_error.glmmTMB | Extract standard errors |
standard_error.merMod | Extract standard errors |
standard_error.MixMod | Extract standard errors |
standard_error_robust | Extract standard errors |