easyViz
Easy Visualization of Conditional Effects from Regression Models
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(), betareg(), and gam() (from 'mgcv'); nonlinear models via nls(); generalized least squares via gls(); and survival models via coxph() (from 'survival'). 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. Approximate confidence intervals for nls() and betareg() models are computed using the delta method. Robust standard errors for rlm() are computed using the sandwich estimator (Zeileis 2004) <doi:10.18637/jss.v011.i10>. For beta regression using 'betareg', see Cribari-Neto and Zeileis (2010) <doi:10.18637/jss.v034.i02>. For mixed-effects models with 'lme4', see Bates et al. (2015) <doi:10.18637/jss.v067.i01>. For models using 'glmmTMB', see Brooks et al. (2017) <doi:10.32614/RJ-2017-066>. Methods for generalized additive models using 'mgcv' follow Wood (2017) <doi:10.1201/9781315370279>.
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autoCRAN-only: this name is served only by autoCRAN, so the count is exact.
CRAN Check Status
Show all 13 flavors
| Flavor | Status |
|---|---|
| r-devel-linux-x86_64-debian-clang | OK |
| r-devel-linux-x86_64-debian-gcc | OK |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | OK |
| r-oldrel-macos-x86_64 | OK |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
Check History
OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
ERROR 12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Jun 8, 2026
examples
Running examples in ‘easyViz-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: easyViz
> ### Title: Easy Visualization of Conditional Effects from Regression Models
> ### Aliases: e
...[truncated]...
rvival)
> library(lme4)
Loading required package: Matrix
Attaching package: ‘lme4’
The following object is masked from ‘package:nlme’:
lmList
> library(glmmTMB)
Error in library(glmmTMB) : there is no package called ‘glmmTMB’
Execution halted
OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
Code
Structure
Lines of code
4,556
Files
16
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
1
Internal functions
28
Testing & CI
Has tests
No
Test-to-code ratio
0.00
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Return-value doc rate
100%
\dontrun example ratio
0%
Roxygen coverage
100%
Has pkgdown
No
NEWS present
Yes
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
–
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
7
First release
2025-07-22
Latest release
2026-03-05
Avg cadence
31 days
Cold removal rate
–
Dep drift
2
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/cran-code-metrics.