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

Compute 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 main functions are ggpredict(), ggemmeans() and ggeffect(). There is a generic plot()-method to plot the results using 'ggplot2'.

Version: 0.9.0
Depends: R (≥ 3.2), graphics, stats, utils
Imports: dplyr, insight, magrittr, MASS, purrr, rlang, scales, sjlabelled (≥ 1.0.17), sjmisc (≥ 2.7.8)
Suggests: AER, betareg, brms, effects (≥ 4.0-0), emmeans, gam, gamm4, gee, ggplot2, GLMMadaptive, glmmTMB, knitr, lme4, Matrix, MCMCglmm, mgcv, nlme, ordinal, prediction, pscl, rmarkdown, rstanarm, rstantools, rstudioapi, sandwich, sjstats, survey, survival, testthat, VGAM
Published: 2019-03-17
Author: Daniel Lüdecke ORCID iD [aut, cre]
Maintainer: Daniel Lüdecke <d.luedecke at>
License: GPL-3
NeedsCompilation: no
Citation: ggeffects citation info
Materials: README NEWS
CRAN checks: ggeffects results


Reference manual: ggeffects.pdf
Vignettes: Difference between ggpredict() and ggemmeans()
Marginal Effects at Specific Values
Marginal Effects of Regression Models
Customize Plot Appearance
Plotting Marginal Effects
Marginal Effects for Random Effects Models
Different Output between Stata and ggeffects
Package source: ggeffects_0.9.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: ggeffects_0.9.0.tgz, r-oldrel: ggeffects_0.9.0.tgz
Old sources: ggeffects archive

Reverse dependencies:

Reverse imports: sjPlot


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