CRAN/E | ggeffects

ggeffects

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

Installation

About

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'.

Citation ggeffects citation info
strengejacke.github.io/ggeffects/
Bug report File report

Key Metrics

Version 1.5.1
R ≥ 3.6
Published 2024-03-26 2 days ago
Needs compilation? no
License MIT
License File
CRAN checks ggeffects results

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Maintainer

Maintainer

Daniel Lüdecke

d.luedecke@uke.de

Authors

Daniel Lüdecke

aut / cre

Frederik Aust

ctb

Sam Crawley

ctb

Mattan S. Ben-Shachar

ctb

Sean C. Anderson

ctb

Material

README
NEWS
Reference manual
Package source

In Views

MixedModels

Vignettes

Documentation of the ggeffects package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ggeffects archive

Depends

R ≥ 3.6

Imports

graphics
insight ≥ 0.19.8
stats
utils

Suggests

AER
aod
bayestestR
betareg
brglm2
brms
broom
car
carData
clubSandwich
datawizard ≥ 0.9.0
effects ≥4.2-2
emmeans ≥ 1.8.9
fixest
gam
gamlss
gamm4
gee
geepack
ggplot2
ggrepel
GLMMadaptive
glmmTMB ≥ 1.1.7
gridExtra
gt
haven
httr
jsonlite
knitr
lme4 ≥ 1.1-35
logistf
magrittr
margins
marginaleffects ≥ 0.16.0
MASS
Matrix
mice
MCMCglmm
mgcv
nestedLogit ≥ 0.3.0
nlme
nnet
ordinal
parameters
parsnip
patchwork
pscl
quantreg
rmarkdown
rms
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Reverse Imports

eirm
INSPECTumours
sjPlot

Reverse Suggests

broom.helpers
insight
nestedLogit
parameters
pubh
sdmTMB
SimplyAgree