rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
Comparison · Analytics
gtsummary vs hstats
A side-by-side editorial comparison of gtsummary and hstats — release velocity, themes, recent moves, and the top alternatives to consider.
gtsummary vs hstats: at a glance
| Feature | gtsummary | hstats |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 0.0 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | clinical-tables, analysis-results-data, regression-summaries, reproducible-reporting | interaction statistics, partial dependence, model explainability, r package |
| Last editorial update | 1h ago | 4h ago |
| Website | Visit → | Visit → |
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.
What is hstats?
hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.
hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.
gtsummary vs hstats: editorial side-by-side
gtsummary
0.0ANALYTICS
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.
hstats
0.0ANALYTICS
hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.
◆ Current state
hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.
◆ Where it's heading
The structural work — the hstats_matrix object, quantile approximation, revised plotting — landed in 1.0.0 just outside this window, and nothing since has changed the package's shape. What continues is model-coverage plumbing: mlr3 classification modes, ranger survival behind a survival argument, and factor predictions added in 1.1.0 then removed again in 1.2.0. The most recent releases are compatibility-driven, tracking ggplot2 rather than the interaction statistics.
◆ Prediction
Expect the next release to be another dependency-compatibility pass or a new model backend working out of the box, rather than new interaction statistics.
Alternatives to gtsummary and hstats
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 gtsummary or hstats.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all gtsummary alternatives → · See all hstats alternatives →
Recent activity from gtsummary and hstats
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agogtsummaryTheme elements no longer evaluated by default
- 8mo agogtsummaryARD strata functions and finer theme control
- 10mo agohstatsggplot 4.0 compatibility and test coverage
- 11mo agogtsummaryPer-level hierarchical sorting and labeled stacking
- 1y agogtsummaryTable splitting, ID labeling, and add_difference_row
- 1y agogtsummaryData pre-processing restored after the 2.0 removal
- 1y agogtsummarytbl_merge gains explicit merge columns
- 1y agohstatsranger survival models supported out of the box
- 2y agohstatsMoves to ModelOriented; factor predictions removed
- 2y agohstatsICE facets for multioutput models; mlr3 fixes
- 2y agohstatsFaster data.frame paths; NaN H-statistics fixed
- 2y agohstatsFactor predictions and line-style 2D partial dependence
Frequently asked questions
What is the difference between gtsummary and hstats?
They serve adjacent needs but don't currently overlap on shipped themes. gtsummary and hstats 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 gtsummary better than hstats?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gtsummary and hstats 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 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.
What are the best alternatives to hstats?
Top hstats alternatives in Analytics are ranked by recent ship velocity. Browse the "hstats alternatives" section above for the current picks, or visit /alternatives/hstats for the full list with editorial commentary on each.