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Comparison · Analytics

modelbased vs rotl

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

modelbased vs rotl: at a glance

Featuremodelbasedrotl
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeseasystats, marginal-effects, contrasts, mixed-modelsopen-tree-of-life, taxonomic-matching, reproducibility, api-tracking
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 rotl?

rotl's whole release history is keeping name matching honest against a moving taxonomy.

Nearly every entry concerns `tnrs_match_names()`, the function that maps user-supplied names onto Open Tree taxonomy ids. 3.1.0 changed which taxon wins a multi-way match — highest matching score rather than lowest OTT id, reversing the rule 3.0.4 introduced. 3.0.12 defaulted `context_name` to 'All life' so a context inferred from the first name could not silently skew later ones. 3.0.11 made a total failure to match return an empty tibble with a warning instead of an error. The rest are small fixes tracking Open Tree API changes.

Read the full rotl trajectory →

modelbased vs rotl: 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.

R
rotl
ANALYTICS
0.0

rotl's whole release history is keeping name matching honest against a moving taxonomy.

◆ Current state

Nearly every entry concerns `tnrs_match_names()`, the function that maps user-supplied names onto Open Tree taxonomy ids. 3.1.0 changed which taxon wins a multi-way match — highest matching score rather than lowest OTT id, reversing the rule 3.0.4 introduced. 3.0.12 defaulted `context_name` to 'All life' so a context inferred from the first name could not silently skew later ones. 3.0.11 made a total failure to match return an empty tibble with a warning instead of an error. The rest are small fixes tracking Open Tree API changes.

◆ Where it's heading

The recurring problem is ambiguity: names match several taxa, and the package has changed its tie-breaking rule twice while making failures and edge cases return predictable objects rather than errors. Nothing here expands what rotl can retrieve; it makes what it retrieves reproducible. The feed also stops in mid-2023, so the package appears dormant.

◆ Prediction

Nothing in the window suggests new capability. If a release comes, the pattern says it will follow an Open Tree API change or another matching-behaviour correction.

Alternatives to modelbased and rotl

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 rotl.

See all modelbased alternatives → · See all rotl alternatives →

Recent activity from modelbased and rotl

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 agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
  4. 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
  5. 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
  6. 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
  7. 3y agorotlrotl 3.1.0 matches on score instead of lowest OTT id
  8. 4y agorotlrotl 3.0.12 defaults matching context to All life
  9. 5y agorotlrotl 3.0.11 returns empty tibble when no names match
  10. 6y agorotlrotl 3.0.10 tracks Open Tree API updates
  11. 7y agorotlrotl 3.0.9 tracks Open Tree API updates
  12. 7y agorotlrotl 3.0.7 updates vignette for TNRS endpoint change

Frequently asked questions

What is the difference between modelbased and rotl?

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

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

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