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ggeffects
Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs
View on CRAN: Click
here
Download and install ggeffects package within the R console
Install from CRAN:
install.packages("ggeffects")
Install from Github:
library("remotes")
install_github("cran/ggeffects") Install by package version:
library("remotes")
install_version("ggeffects", "2.3.2") Attach the package and use:
library("ggeffects")
Maintained by
Daniel Lüdecke
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-04-26
Latest Update: 2025-06-13
Description:
Compute marginal effects and adjusted predictions from statistical
models and returns the result as tidy data frames. These data frames are
ready to use with the 'ggplot2'-package. Effects and predictions can be
calculated for many different models. Interaction terms, splines and
polynomial terms are also supported. The main functions are ggpredict(),
ggemmeans() and ggeffect(). There is a generic plot()-method to plot the
results using 'ggplot2'.
How to cite:
Daniel Lüdecke (2017). ggeffects: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs. R package version 2.3.2, https://cran.r-project.org/web/packages/ggeffects. Accessed 07 Mar. 2026.
Previous versions and publish date:
0.1.0 (2017-04-26 19:23), 0.1.1 (2017-05-17 11:28), 0.1.2 (2017-06-19 12:06), 0.2.0 (2017-07-24 14:26), 0.2.1 (2017-08-22 16:06), 0.2.2 (2017-09-20 02:09), 0.3.0 (2017-11-27 19:33), 0.3.1 (2018-01-15 15:36), 0.3.2 (2018-03-21 14:41), 0.3.3 (2018-05-03 20:10), 0.3.4 (2018-06-08 12:12), 0.4.0 (2018-07-03 13:50), 0.5.0 (2018-08-11 10:10), 0.6.0 (2018-10-11 09:10), 0.7.0 (2018-11-17 11:20), 0.8.0 (2019-01-09 17:20), 0.9.0 (2019-03-17 15:20), 0.10.0 (2019-05-13 15:30), 0.11.0 (2019-07-01 12:20), 0.12.0 (2019-09-03 15:40), 0.13.0 (2019-11-08 14:30), 0.14.0 (2019-12-16 07:10), 0.14.1 (2020-01-28 15:30), 0.14.2 (2020-03-14 22:00), 0.14.3 (2020-04-20 08:10), 0.15.0 (2020-06-16 18:30), 0.15.1 (2020-07-27 12:00), 0.16.0 (2020-09-13 16:00), 1.0.0 (2020-11-29 22:00), 1.0.1 (2020-12-14 09:30), 1.0.2 (2021-03-17 12:00), 1.1.0 (2021-04-30 06:10), 1.1.1 (2021-07-29 15:40), 1.1.2 (2022-04-10 23:32), 1.1.3 (2022-08-07 15:00), 1.1.4 (2022-10-23 21:55), 1.1.5 (2023-01-25 14:10), 1.2.0 (2023-02-24 12:00), 1.2.1 (2023-04-02 17:50), 1.2.2 (2023-05-04 11:00), 1.2.3 (2023-06-11 15:20), 1.3.0 (2023-08-21 16:00), 1.3.1 (2023-09-05 22:00), 1.3.2 (2023-10-17 12:30), 1.3.3 (2023-12-15 09:20), 1.3.4 (2023-12-18 10:10), 1.4.0 (2024-02-05 18:30), 1.5.0 (2024-02-24 17:10), 1.5.1 (2024-03-26 06:50), 1.5.2 (2024-04-15 11:40), 1.6.0 (2024-05-18 22:00), 1.7.0 (2024-06-20 18:00), 1.7.1 (2024-09-01 22:00), 1.7.2 (2024-10-13 13:10), 2.0.0 (2024-11-27 12:40), 2.1.0 (2025-01-20 11:50), 2.2.0 (2025-02-05 23:40), 2.2.1 (2025-03-11 23:30), 2.3.0 (2025-06-13 12:40), 2.3.1 (2025-08-20 22:20)
Other packages that cited ggeffects R package
View ggeffects citation profile
Other R packages that ggeffects depends,
imports, suggests or enhances
Complete documentation for ggeffects
Functions, R codes and Examples using
the ggeffects R package
Some associated functions: collapse_by_group . efc . fish . get_title . ggpredict . hypothesis_test . install_latest . johnson_neyman . lung2 . new_data . plot . pool_comparisons . pool_predictions . pretty_range . residualize_over_grid . values_at . vcov .
Some associated R codes: backports.R . collapse_re_data.R . data_frame_methods.R . efc.R . emmeans_prediction_data.R . fish.R . get_predictions_MCMCglmm.R . get_predictions_MixMod.R . get_predictions_bamlss.R . get_predictions_bayesx.R . get_predictions_cgam.R . get_predictions_clm.R . get_predictions_clm2.R . get_predictions_clmm.R . get_predictions_coxph.R . get_predictions_gam.R . get_predictions_gam2.R . get_predictions_gamlss.R . get_predictions_gee.R . get_predictions_geeglm.R . get_predictions_generic.R . get_predictions_generic2.R . get_predictions_glimML.R . get_predictions_glm.R . get_predictions_glmRob.R . get_predictions_glmmTMB.R . get_predictions_glmrob_base.R . get_predictions_lm.R . get_predictions_lme.R . get_predictions_lmrob_base.R . get_predictions_logistf.R . get_predictions_logitr.R . get_predictions_lrm.R . get_predictions_mclogit.R . get_predictions_merMod.R . get_predictions_mixor.R . get_predictions_mlogit.R . get_predictions_multinom.R . get_predictions_nestedLogit.R . get_predictions_ols.R . get_predictions_polr.R . get_predictions_rq.R . get_predictions_rqs.R . get_predictions_sdmTMB.R . get_predictions_stan.R . get_predictions_survival.R . get_predictions_svyglm.R . get_predictions_svyglmnb.R . get_predictions_tobit.R . get_predictions_vgam.R . get_predictions_vglm.R . get_predictions_wbm.R . get_predictions_zelig.R . get_predictions_zeroinfl.R . getter.R . ggaverage.R . ggeffect.R . ggemmeans.R . ggemmeans_add_confint.R . ggemmeans_zi_predictions.R . ggpredict.R . hypothesis_test.R . install_latest.R . johnson_neyman.R . moderator_pattern.R . new_data.R . plot.R . pool_comparisons.R . pool_predictions.R . post_processing_labels.R . post_processing_predictions.R . predict_zero_inflation.R . predictions.R . pretty_range.R . print.R . residualize_over_grid.R . sanitize_type_arg.R . simulate_predictions.R . standard_error_predictions.R . themes.R . utils.R . utils_check_transformations.R . utils_colors.R . utils_get_cleaned_terms.R . utils_get_data_grid.R . utils_get_representative_values.R . utils_ggpredict.R . utils_handle_labels.R . utils_is_empty.R . utils_model_function.R . utils_reshape.R . utils_select.R . utils_set_attr.R . utils_typical_value.R . vcov.R . Full ggeffects package functions and examples
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