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'.
Version: | 1.1.0 |
Depends: | R (≥ 3.4) |
Imports: | graphics, insight (≥ 0.13.0), MASS, sjlabelled (≥ 1.1.2), stats |
Suggests: | AER, aod, betareg, brms, clubSandwich, effects (≥ 4.1-2), emmeans (≥ 1.4.1), gam, gamlss, gamm4, gee, geepack, ggplot2, GLMMadaptive, glmmTMB (≥ 1.0.0), gridExtra, haven, httr, knitr, lme4, logistf, magrittr, margins, Matrix, mice, MCMCglmm, mgcv, nlme, ordinal, parameters, prediction, pscl, quantreg, rmarkdown, rms, robustbase, rstanarm, rstantools, sandwich, see, sjstats, sjmisc (≥ 2.8.2), survey, survival, testthat, VGAM |
Published: | 2021-04-30 |
Author: | Daniel Lüdecke |
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 |
Reverse imports: | drhur, sjPlot |
Reverse suggests: | pubh |
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