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easyViz
View on CRAN: Click
here
Download and install easyViz package within the R console
Install from CRAN:
install.packages("easyViz")
Install from Github:
library("remotes")
install_github("cran/easyViz") Install by package version:
library("remotes")
install_version("easyViz", "2.1.0") Attach the package and use:
library("easyViz")
Maintained by
Luca Corlatti
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-07-22
Latest Update: 2025-07-22
Description:
Offers a flexible and user-friendly interface for visualizing conditional effects from a broad range of regression models, including mixed-effects and generalized additive (mixed) models. Compatible model types include lm(), rlm(), glm(), glm.nb(), and gam() (from 'mgcv'); nonlinear models via nls(); and generalized least squares via gls(). Mixed-effects models with random intercepts and/or slopes can be fitted using lmer(), glmer(), glmer.nb(), glmmTMB(), or gam() (from 'mgcv', via smooth terms). Plots are rendered using base R graphics with extensive customization options. Robust standard errors for rlm() are computed using the sandwich estimator (Zeileis 2004) <doi:10.18637/jss.v011.i10>. For mixed models using 'glmmTMB', see Brooks et al. (2017) <doi:10.32614/RJ-2017-066>. For linear mixed-effects models with 'lme4', see Bates et al. (2015) <doi:10.18637/jss.v067.i01>. Methods for generalized additive models follow Wood (2017) <doi:10.1201/9781315370279>.
How to cite:
Luca Corlatti (2025). easyViz: Easy Visualization of Conditional Effects from Regression Models. R package version 2.1.0, https://cran.r-project.org/web/packages/easyViz. Accessed 07 Oct. 2026.
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