rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
ggraph vs modelbased
A side-by-side editorial comparison of ggraph and modelbased — release velocity, themes, recent moves, and the top alternatives to consider.
ggraph vs modelbased: at a glance
What is ggraph?
ggraph has settled into ggplot2 compatibility duty
ggraph provides the grammar of graphics for network and tree data. Its recent releases are compatibility and bug-fix work — a collapse fix in get_edges() alongside ggplot2 v4.0.0 upkeep, and before that a pipe rollback. The last release with real content was 2.2.0, a long list of layout and edge-geom corrections.
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.
ggraph vs modelbased: editorial side-by-side
ggraph
0.0ANALYTICS
ggraph has settled into ggplot2 compatibility duty
◆ Current state
ggraph provides the grammar of graphics for network and tree data. Its recent releases are compatibility and bug-fix work — a collapse fix in get_edges() alongside ggplot2 v4.0.0 upkeep, and before that a pipe rollback. The last release with real content was 2.2.0, a long list of layout and edge-geom corrections.
◆ Where it's heading
The feature surface looks finished and the maintenance is about keeping it working under a moving ggplot2. The one architectural move in this window — pushing dendrogram layout into compiled code to escape R's recursion limits, back in 2.1.0 — was about scaling existing features, not adding new ones.
◆ Prediction
Expect the next release to follow ggplot2 4.0.0 rather than introduce layouts or edge geoms.
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 ggraph 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 ggraph 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 ggraph alternatives → · See all modelbased alternatives →
Recent activity from ggraph 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
- 11mo agoggraphget_edges() collapse fix and ggplot2 v4 upkeep
- 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
- 2y agoggraphNative pipe usage rolled back
- 2y agoggraphLayout precision and edge geom fixes across the package
- 3y agoggraphBinned edge scales and compiled dendrogram layouts
- 5y agoggraphC++11 pinned to fix std::random_shuffle deprecation
- 5y agoggraphFaceting and edge geom bug fixes
Frequently asked questions
What is the difference between ggraph and modelbased?
They serve adjacent needs but don't currently overlap on shipped themes. ggraph 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 ggraph better than modelbased?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggraph 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 ggraph?
Top ggraph alternatives in Analytics are ranked by recent ship velocity. Browse the "ggraph alternatives" section above for the current picks, or visit /alternatives/ggraph 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.