rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
easystats vs modelbased
A side-by-side editorial comparison of easystats and modelbased — release velocity, themes, recent moves, and the top alternatives to consider.
easystats vs modelbased: at a glance
What is easystats?
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
easystats is the meta-package for the easystats ecosystem, which spans insight, parameters, performance and their siblings. It ships almost no statistics of its own; its releases add installation helpers, ecosystem introspection functions and vignettes. The consequential release in this window is 0.7.0, which moved the whole ecosystem to an MIT license.
What is modelbased?
modelbased is turning marginal effects into a full contrast grammar
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
easystats vs modelbased: editorial side-by-side
easystats
0.0ANALYTICS
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
◆ Current state
easystats is the meta-package for the easystats ecosystem, which spans insight, parameters, performance and their siblings. It ships almost no statistics of its own; its releases add installation helpers, ecosystem introspection functions and vignettes. The consequential release in this window is 0.7.0, which moved the whole ecosystem to an MIT license.
◆ Where it's heading
Work concentrates on making the ecosystem legible and installable as a unit: easystats_packages() to enumerate it, easystats_citations() to count its citations, pak and r-universe support to install it, and a complete-workflow vignette to show it in use. Underneath that, 0.7.0 settled the licensing and formalized the author list. The pattern is a project tending its own boundaries rather than adding capability.
◆ Prediction
The recent additions are all introspection and installation helpers, so the next release most likely adds another of those or refreshes component versions rather than changing what the ecosystem does.
modelbased
0.0ANALYTICS
modelbased is turning marginal effects into a full contrast grammar
◆ Current state
modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.
◆ Where it's heading
The package is building a compositional vocabulary rather than a fixed menu — contrasts of average slopes, contrasts across two numeric predictors, inequality summaries across all outcome categories, and now user-supplied post-processing of comparisons. Support quietly widens underneath, covering nestedLogit, brms finite mixtures, and offsets under population and average estimation. Plotting gets attention in proportion to how often these results are presented rather than tabulated, including collapse_by_group() for showing averaged raw data under mixed-model fits.
◆ Prediction
With post_process and omnibus tests both landed, the likely next step is making these composed comparisons easier to report — formatting or plotting methods for the multi-step results rather than new comparison types.
Alternatives to easystats and modelbased
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either easystats or modelbased.
writexl
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rgbif
rgbif is steadily pushing users off paged searching and onto real downloads.
rstanarm
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
See all easystats alternatives → · See all modelbased alternatives →
Recent activity from easystats and modelbased
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
- 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
- 5mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
- 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
- 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
- 1y agoeasystatseasystats_citations() added; install_latest() gains a github source
- 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
- 1y agoeasystatsComplete-workflow vignette added; install_suggested() fix
- 2y agoeasystatseasystats_packages() added; pak used for installs when available
- 2y agoeasystatsR version policy vignette added
- 2y agoeasystatsFix for development package version detection
- 2y agoeasystatsEcosystem relicensed to MIT; two new authors added ⚡
Frequently asked questions
What is the difference between easystats and modelbased?
They serve adjacent needs but don't currently overlap on shipped themes. easystats and modelbased are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is easystats better than modelbased?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. easystats and modelbased are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to easystats?
Top easystats alternatives in Analytics are ranked by recent ship velocity. Browse the "easystats alternatives" section above for the current picks, or visit /alternatives/easystats for the full list with editorial commentary on each.
What are the best alternatives to modelbased?
Top modelbased alternatives in Analytics are ranked by recent ship velocity. Browse the "modelbased alternatives" section above for the current picks, or visit /alternatives/modelbased for the full list with editorial commentary on each.