[aut, cre]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 [aut, cre] |
| Maintainer: | Daniel Lüdecke <d.luedecke at uke.de> |
| BugReports: | https://github.com/strengejacke/ggeffects/issues |
| License: | GPL-3 |
| URL: | https://strengejacke.github.io/ggeffects |
| 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: ggeffects_0.9.0.zip, r-release: ggeffects_0.9.0.zip, r-oldrel: ggeffects_0.9.0.zip |
| OS X binaries: | r-release: ggeffects_0.9.0.tgz, r-oldrel: ggeffects_0.9.0.tgz |
| Old sources: | ggeffects archive |
| Reverse imports: | sjPlot |
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