Checks if all objects are models of same class
Color-formatting for data columns based on condition
Generic export of data frames into formatted tables
Gather information about objects in ellipsis (dot dot dot)
Find auxiliary (distributional) parameters from models
Find names of model parameters from Bayesian models
Find model parameters from models with special components
Find names of model parameters from marginal effects models
Find model parameters from estimated marginal means objects
Find names of model parameters from generalized additive models
Find names of model parameters from mixed models
Find names of model parameters from zero-inflated models
Find possible transformation of model variables
Capitalizes the first letter in a string
Probability of direction (pd) formatting
Get the data that was used to fit the model
Extract a reference grid from objects created by '{emmeans}' and '{marginaleffects}'
Extract various information from mixed models
Get a model objects that is saved as attribute
Get model parameters from Bayesian models
Get model parameters from marginal effects models
Get model parameters from models with special components
Get model parameters from estimated marginal means objects
Get model parameters from generalized additive models
Get model parameters from zero-inflated and hurdle models
Model predictions (robust) and their confidence intervals
Confidence intervals around predicted values
Get the values from the response variable
Get residual standard deviation from models
Return function of transformed response variables
Get variance-covariance matrix from models
Get variance components from random effects models
insight: A Unified Interface to Access Information from Model Objects in R.
Convergence test for mixed effects models
Checks if a model is a generalized additive model
Checks if a model is a mixed effects model
Checks if an object is a regression model or statistical test object
Checks if a regression model object is supported by the insight package
Checks if an object stems from a multivariate response model
Checks whether a list of models are nested models
Checks if model is a null-model (intercept-only)
Get link-inverse function from model object
Count number of random effect levels in a mixed model
Compute intercept-only model for regression models
Prepare summary statistics of model parameters for printing
Validate arguments against a given set of options