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

Compute marginal effects at the mean or average marginal effects from statistical models and returns the result as tidy data frames. These data frames are ready to use with the 'ggplot2'-package. Marginal effects can be calculated for many different models. Interaction terms, splines and polynomial terms are also supported. The two main functions are 'ggpredict()' and 'ggaverage()', however, there are some convenient wrapper-functions especially for polynomials or interactions. There is a generic 'plot()'-method to plot the results using 'ggplot2'.


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0.2.2 by Daniel Lüdecke, a day ago

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Authors: Daniel Lüdecke <>

Documentation:   PDF Manual  

GPL-3 license

Imports dplyr, effects, ggplot2, magrittr, prediction, purrr, rlang, scales, sjlabelled, sjmisc, sjstats, tibble, tidyr

Depends on stats, utils

Suggests knitr, MASS, rmarkdown, rstanarm, snakecase

Imported by sjPlot.

See at CRAN