Reference

Adjusted Predictions and Marginal Means for Regression Models
predict_response()	Adjusted predictions and estimated marginal means from regression models
as.data.frame(<ggeffects>) ggaverage() ggeffect() ggemmeans() ggpredict()	Adjusted predictions from regression models
pool_predictions()	Pool Predictions or Estimated Marginal Means
Pairwise Comparisons, Contrasts and Marginal Effects
test_predictions() hypothesis_test()	(Pairwise) comparisons between predictions (marginal effects)
pool_comparisons()	Pool contrasts and comparisons from test_predictions()
Plotting Adjusted Predictions
plot(<ggeffects>) theme_ggeffects() ggeffects_palette() show_palettes()	Plot ggeffects-objects
Data Grids and Meaningful Values
collapse_by_group()	Collapse raw data by random effect groups
new_data() data_grid()	Create a data frame from all combinations of predictor values
pretty_range()	Create a pretty sequence over a range of a vector
residualize_over_grid()	Compute partial residuals from a data grid
values_at() representative_values()	Calculate representative values of a vector
Printing and Formatting Output
format(<ggeffects>) format(<ggcomparisons>) print(<ggeffects>) print_md(<ggeffects>) print_html(<ggeffects>) print(<ggcomparisons>) print_html(<ggcomparisons>) print_md(<ggcomparisons>)	Print and format ggeffects-objects
reexports print_html print_md	Objects exported from other packages
Plot Annotation from Labelled Data
get_title() get_x_title() get_y_title() get_legend_title() get_legend_labels() get_x_labels() get_complete_df()	Get titles and labels from data
Utilities
get_predictions()	S3-class definition for the ggeffects package
install_latest()	Update latest ggeffects-version from R-universe (GitHub) or CRAN
vcov(<ggeffects>)	Calculate variance-covariance matrix for adjusted predictions
Sample Data Sets
coffee_data	Sample dataset from a course about analysis of factorial designs
efc efc_test	Sample dataset from the EUROFAMCARE project
fish	Sample data set
lung2	Sample data set