R: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs

# Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs

## Documentation for package ‘ggeffects’ version 2.3.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

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
data_grid | Create a data frame from all combinations of predictor values
efc | Sample dataset from the EUROFAMCARE project
efc_test | Sample dataset from the EUROFAMCARE project
fish | Sample data set
format.ggcomparisons | Print and format ggeffects-objects
format.ggeffects | Print and format ggeffects-objects
get_complete_df | Get titles and labels from data
get_legend_labels | Get titles and labels from data
get_legend_title | Get titles and labels from data
get_predictions | S3-class definition for the ggeffects package
get_predictions.default | S3-class definition for the ggeffects package
get_title | Get titles and labels from data
get_x_labels | Get titles and labels from data
get_x_title | Get titles and labels from data
get_y_title | Get titles and labels from data
ggaverage | Adjusted predictions from regression models
ggeffect | Adjusted predictions from regression models
ggeffects_palette | Plot ggeffects-objects
ggemmeans | Adjusted predictions from regression models
ggpredict | Adjusted predictions from regression models
hypothesis_test | (Pairwise) comparisons between predictions (marginal effects)
install_latest | Update latest ggeffects-version from R-universe (GitHub) or CRAN
lung2 | Sample data set
new_data | Create a data frame from all combinations of predictor values
plot | Plot ggeffects-objects
plot.ggeffects | 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
print | Print and format ggeffects-objects
print.ggcomparisons | Print and format ggeffects-objects
print.ggeffects | Print and format ggeffects-objects
print_html.ggcomparisons | Print and format ggeffects-objects
print_html.ggeffects | Print and format ggeffects-objects
print_md.ggcomparisons | Print and format ggeffects-objects
print_md.ggeffects | Print and format ggeffects-objects
representative_values | Calculate representative values of a vector
residualize_over_grid | Compute partial residuals from a data grid
residualize_over_grid.data.frame | Compute partial residuals from a data grid
residualize_over_grid.ggeffects | Compute partial residuals from a data grid
show_palettes | Plot ggeffects-objects
test_predictions | (Pairwise) comparisons between predictions (marginal effects)
test_predictions.default | (Pairwise) comparisons between predictions (marginal effects)
test_predictions.ggeffects | (Pairwise) comparisons between predictions (marginal effects)
theme_ggeffects | Plot ggeffects-objects
values_at | Calculate representative values of a vector
vcov | Calculate variance-covariance matrix for adjusted predictions
vcov.ggeffects | Calculate variance-covariance matrix for adjusted predictions