rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
dtplyr vs modelbased
A side-by-side editorial comparison of dtplyr and modelbased — release velocity, themes, recent moves, and the top alternatives to consider.
dtplyr vs modelbased: at a glance
What is dtplyr?
dtplyr stopped hijacking data.table objects and became an opt-in translator
dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.
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.
dtplyr vs modelbased: editorial side-by-side
dtplyr
0.0ANALYTICS
dtplyr stopped hijacking data.table objects and became an opt-in translator
◆ Current state
dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.
◆ Where it's heading
The package is trailing dplyr's own feature releases rather than leading them, adding each new verb once it settles upstream. Performance work is targeted at specific verbs where data.table has a faster primitive: setorder() for arrange(), reference drops for select(), rleid() for consecutive_id(). Release cadence has thinned considerably since 2023.
◆ Prediction
Expect further one-for-one translations as dplyr adds verbs, and continued fixes around .by and non-standard column names; the entries show no sign of a broader redesign.
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 dtplyr 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 dtplyr 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 dtplyr alternatives → · See all modelbased alternatives →
Recent activity from dtplyr 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 agodtplyrreframe(), case_match() and consecutive_id() gain translations
- 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
- 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
- 3y agodtplyrcrayon dependency dropped
- 3y agodtplyrVerbs stop auto-dispatching; lazy_dt() now required ⚡
- 3y agodtplyrdtplyr 1.2.2
- 4y agodtplyrdtplyr 1.2.1
- 4y agodtplyrEight tidyr verbs gain data.table translations
Frequently asked questions
What is the difference between dtplyr and modelbased?
They serve adjacent needs but don't currently overlap on shipped themes. dtplyr 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 dtplyr better than modelbased?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dtplyr 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 dtplyr?
Top dtplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "dtplyr alternatives" section above for the current picks, or visit /alternatives/dtplyr 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.