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modelbased vs taxize

A side-by-side editorial comparison of modelbased and taxize — release velocity, themes, recent moves, and the top alternatives to consider.

modelbased vs taxize: at a glance

Featuremodelbasedtaxize
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeseasystats, marginal-effects, contrasts, mixed-modelstaxonomy, api-aggregation, upstream-churn, deprecation
Last editorial update1h ago55m ago
WebsiteVisit →Visit →

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.

Read the full modelbased trajectory →

What is taxize?

taxize spends its releases absorbing other people's API changes, one dead source at a time.

The most recent work is migration: 0.10.0 replaced the deprecated Global Names Resolver functions with GNA equivalents (`gna_verifier`, `gna_parse`), rewrote `scrapenames` for the new API, and updated its rredlist usage to match that package's own v4 rewrite. 0.10.1 then tuned `gna_verifier`'s batch size to 50. The older entries in the window show the same shape from a different angle: `tnrs()` made defunct because the service died, COL dropped over rate limiting, NatureServe reworked for a new API, and a package-wide parameter rename to `sci` / `com` / `id` / `sci_com` / `sci_id`.

Read the full taxize trajectory →

modelbased vs taxize: editorial side-by-side

M
modelbased
ANALYTICS
0.0

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.

T
taxize
ANALYTICS
0.0

taxize spends its releases absorbing other people's API changes, one dead source at a time.

◆ Current state

The most recent work is migration: 0.10.0 replaced the deprecated Global Names Resolver functions with GNA equivalents (`gna_verifier`, `gna_parse`), rewrote `scrapenames` for the new API, and updated its rredlist usage to match that package's own v4 rewrite. 0.10.1 then tuned `gna_verifier`'s batch size to 50. The older entries in the window show the same shape from a different angle: `tnrs()` made defunct because the service died, COL dropped over rate limiting, NatureServe reworked for a new API, and a package-wide parameter rename to `sci` / `com` / `id` / `sci_com` / `sci_id`.

◆ Where it's heading

taxize's job is aggregating a dozen taxonomic databases, so most of its engineering is downstream of decisions it does not control — sources go away, endpoints change, rate limits appear. The visible trend is consolidation: fewer, better-maintained backends rather than broader coverage. Release cadence has thinned to roughly one a year, and the rredlist coupling means it now inherits that package's breaking changes too.

◆ Prediction

Expect the next release to track another upstream source change rather than add new databases; the deprecated-parameter aliases from the 0.9.97 rename are also overdue for removal.

Alternatives to modelbased and taxize

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 modelbased or taxize.

See all modelbased alternatives → · See all taxize alternatives →

Recent activity from modelbased and taxize

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
  2. 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
  3. 5mo agotaxizetaxize 0.10.1 lowers gna_verifier batch size
  4. 5mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
  5. 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
  6. 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
  7. 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
  8. 1y agotaxizetaxize 0.10.0 migrates to GNA and the new rredlist API
  9. 5y agotaxizetaxize 0.9.99 retires tnrs(), paginates WORMS queries
  10. 5y agotaxizetaxize 0.9.98 adds NCBI and zoological rank names
  11. 6y agotaxizetaxize 0.9.97 standardises parameter names package-wide
  12. 6y agotaxizetaxize 0.9.96 updates NatureServe for its new API

Frequently asked questions

What is the difference between modelbased and taxize?

They serve adjacent needs but don't currently overlap on shipped themes. modelbased and taxize 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 modelbased better than taxize?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. modelbased and taxize 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 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.

What are the best alternatives to taxize?

Top taxize alternatives in Analytics are ranked by recent ship velocity. Browse the "taxize alternatives" section above for the current picks, or visit /alternatives/taxize for the full list with editorial commentary on each.