bootstrap_model | Model bootstrapping |
bootstrap_parameters | Parameters bootstrapping |
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.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.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 |
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 |
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 |
efa_to_cfa | Conversion between EFA results and CFA structure |
equivalence_test.lm | Equivalence test |
factor_analysis | Factor Analysis (FA) |
fish | Sample data set |
format_algorithm | Model Algorithm formatting |
format_bf | Bayes Factor 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 | Parameter names formatting |
format_pd | Probability of direction (pd) formatting |
format_rope | Percentage in ROPE formatting |
get_scores | Get Scores from Principal Component Analysis (PCA) |
kurtosis | Compute Skewness and Kurtosis |
model_parameters | Model Parameters |
model_parameters.aov | Parameters from ANOVAs |
model_parameters.befa | Parameters from PCA/FA |
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.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.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.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_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 |
parameters | Model Parameters |
parameters_table | Parameter table formatting |
parameters_type | Type of model parameters |
principal_components | Principal Component Analysis (PCA) |
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.clm2 | p-values |
p_value.default | p-values |
p_value.DirichletRegModel | 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.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 |
qol_cancer | Sample data set |
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 |
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 |
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.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.zeroinfl | Standard Errors |
standard_error_robust | Robust estimation |