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collapse vs gtsummary

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

Shared themes:r-package

collapse vs gtsummary: at a glance

Featurecollapsegtsummary
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticsclinical-tables, analysis-results-data, regression-summaries, reproducible-reporting
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is collapse?

collapse got a JSS paper and a 7x fmean speedup in the same release.

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

Read the full collapse trajectory →

What is gtsummary?

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

Read the full gtsummary trajectory →

collapse vs gtsummary: editorial side-by-side

C
collapse
ANALYTICS
0.0

collapse got a JSS paper and a 7x fmean speedup in the same release.

◆ Current state

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

◆ Where it's heading

The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.

◆ Prediction

Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.

G
gtsummary
ANALYTICS
0.0

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

◆ Current state

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

◆ Where it's heading

The ARD work is the through-line. Table IDs exist so gather_ard() can return a named list; hierarchical tables gained per-level sorting and targeted filtering; ARD inputs are pre-processed so sorting applies to non-standard shapes. The package is becoming a structured-results engine that happens to render tables, rather than a renderer alone. Alongside that, 2.2.0 restored data pre-processing that 2.0 had removed after the reduced functionality hurt users — a maintainer willing to reverse a major-version decision.

◆ Prediction

Expect the hierarchical and ARD functions, introduced as a preview without a full deprecation cycle, to keep stabilizing toward a settled API rather than new table types appearing.

Alternatives to collapse and gtsummary

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 collapse or gtsummary.

See all collapse alternatives → · See all gtsummary alternatives →

Recent activity from collapse and gtsummary

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

  1. 2mo agogtsummaryTheme elements no longer evaluated by default
  2. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  3. 7mo agocollapseNegative zero now hashes equal to zero across the package
  4. 8mo agogtsummaryARD strata functions and finer theme control
  5. 8mo agocollapsecollap() no longer double-aggregates external weights
  6. 9mo agocollapseCustom unlist() preserves attributes
  7. 11mo agogtsummaryPer-level hierarchical sorting and labeled stacking
  8. 0y agocollapseAssorted bug fixes
  9. 1y agogtsummaryTable splitting, ID labeling, and add_difference_row
  10. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  11. 1y agogtsummaryData pre-processing restored after the 2.0 removal
  12. 1y agogtsummarytbl_merge gains explicit merge columns

Frequently asked questions

What is the difference between collapse and gtsummary?

Both compete on the same themes — r-package — within Analytics. collapse and gtsummary 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 collapse better than gtsummary?

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

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

What are the best alternatives to gtsummary?

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