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: |
1.1.3 |
Depends: |
R (≥ 3.4) |
Imports: |
graphics, insight (≥ 0.17.0), 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, patchwork, prediction, pscl, quantreg, rmarkdown, rms, robustbase, rstanarm, rstantools, sandwich, see, sjstats, sjmisc (≥
2.8.2), survey, survival, testthat, VGAM |
Published: |
2022-08-07 |
Author: |
Daniel Lüdecke
[aut, cre],
Frederik Aust
[ctb],
Sam Crawley [ctb],
Mattan S. Ben-Shachar
[ctb] |
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 |