as.data.frame.ggeffects
                        Adjusted predictions from regression models
coffee_data             Sample dataset from a course about analysis of
                        factorial designs
collapse_by_group       Collapse raw data by random effect groups
efc                     Sample dataset from the EUROFAMCARE project
fish                    Sample data set
format.ggeffects        Print and format ggeffects-objects
get_title               Get titles and labels from data
install_latest          Update latest ggeffects-version from R-universe
                        (GitHub) or CRAN
johnson_neyman          Spotlight-analysis: Create Johnson-Neyman
                        confidence intervals and plots
lung2                   Sample data set
new_data                Create a data frame from all combinations of
                        predictor values
plot                    Plot ggeffects-objects
pool_comparisons        Pool contrasts and comparisons from
                        'test_predictions()'
pool_predictions        Pool Predictions or Estimated Marginal Means
predict_response        Adjusted predictions and estimated marginal
                        means from regression models
pretty_range            Create a pretty sequence over a range of a
                        vector
residualize_over_grid   Compute partial residuals from a data grid
test_predictions        (Pairwise) comparisons between predictions
                        (marginal effects)
values_at               Calculate representative values of a vector
vcov                    Calculate variance-covariance matrix for
                        adjusted predictions
