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


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Documentation for package ‘ggeffects’ version 1.3.3

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as.data.frame.ggeffects Marginal effects, adjusted predictions and estimated marginal means from regression models
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
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_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 Marginal effects, adjusted predictions and estimated marginal means from regression models
ggeffect Marginal effects, adjusted predictions and estimated marginal means from regression models
ggemmeans Marginal effects, adjusted predictions and estimated marginal means from regression models
ggpredict Marginal effects, adjusted predictions and estimated marginal means from regression models
hypothesis_test (Pairwise) comparisons between predictions
hypothesis_test.default (Pairwise) comparisons between predictions
hypothesis_test.ggeffects (Pairwise) comparisons between predictions
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
plot.ggeffects Plot ggeffects-objects
plot.ggjohnson_neyman Spotlight-analysis: Create Johnson-Neyman confidence intervals and plots
pool_comparisons Pool contrasts and comparisons from 'hypothesis_test()'
pool_predictions Pool Predictions or Estimated Marginal Means
pretty_range Create a pretty sequence over a range of a vector
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_pals Plot ggeffects-objects
spotlight_analysis Spotlight-analysis: Create Johnson-Neyman confidence intervals and plots
test_predictions (Pairwise) comparisons between predictions
theme_ggeffects Plot ggeffects-objects
values_at Calculate representative values of a vector
vcov Calculate variance-covariance matrix for marginal effects
vcov.ggeffects Calculate variance-covariance matrix for marginal effects