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admiralmetabolic vs ggsurvfit

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

admiralmetabolic vs ggsurvfit: at a glance

Featureadmiralmetabolicggsurvfit
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themespharmaverse, cdisc-adam, obesity, clinical-templatessurvival-analysis, ggplot2, competing-risks, clinical-plots
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is admiralmetabolic?

admiralmetabolic has covered its core obesity derivations and moved to upkeep.

Three releases in thirteen months took the package from two anthropometric ratio derivations to ADVS, ADCOEQ and ADLB templates with matching vignettes and shared SDTM test data. The February 2026 release contains no new functions — a template path fix, a CRAN relative-path fix, central lint configuration, and the kapa.ai Ask AI widget added across admiral documentation.

Read the full admiralmetabolic trajectory →

What is ggsurvfit?

ggsurvfit is in correctness-and-compatibility mode, not feature mode.

The package draws survival and cumulative-incidence curves on a ggplot2 grammar, with risk tables, p-values and quantile annotations. Recent releases are entirely fixes and upstream tracking: ggplot2 v4.0.0 compatibility in 2025, and a 2026 patch correcting a Gray-test p-value that could be reported for the wrong competing event.

Read the full ggsurvfit trajectory →

admiralmetabolic vs ggsurvfit: editorial side-by-side

A0.0

admiralmetabolic has covered its core obesity derivations and moved to upkeep.

◆ Current state

Three releases in thirteen months took the package from two anthropometric ratio derivations to ADVS, ADCOEQ and ADLB templates with matching vignettes and shared SDTM test data. The February 2026 release contains no new functions — a template path fix, a CRAN relative-path fix, central lint configuration, and the kapa.ai Ask AI widget added across admiral documentation.

◆ Where it's heading

The package is consolidating into the pharmaverse ecosystem rather than growing its own surface: test datasets moved out to pharmaversesdtm, lint configuration moved to admiraldev, and documentation now points back at the shared admiral ecosystem page. What stays package-specific is the metabolic derivations themselves.

◆ Prediction

With no metabolic-specific derivations in the latest release, the next cycle looks more likely to bring another dataset or template than new functions.

G
ggsurvfit
ANALYTICS
2.5

ggsurvfit is in correctness-and-compatibility mode, not feature mode.

◆ Current state

The package draws survival and cumulative-incidence curves on a ggplot2 grammar, with risk tables, p-values and quantile annotations. Recent releases are entirely fixes and upstream tracking: ggplot2 v4.0.0 compatibility in 2025, and a 2026 patch correcting a Gray-test p-value that could be reported for the wrong competing event.

◆ Where it's heading

The feature surface settled around 1.0.0, when risk-table alignment was exported and colour and linetype defaults became configurable. Since then the work is keeping pace with survival, ggplot2 and tidycmprsk changes, and closing cases where the plotted curve and the annotation disagreed — the p-value matched by position rather than name, confidence limits swapped for multi-state models, quantiles read off a plateau.

◆ Prediction

Expect the next release to track upstream survival or ggplot2 changes rather than add plotting features; the CDISC censoring convention adopted in Surv_CNSR() suggests further alignment with clinical data standards is the likelier direction.

Alternatives to admiralmetabolic and ggsurvfit

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 admiralmetabolic or ggsurvfit.

See all admiralmetabolic alternatives → · See all ggsurvfit alternatives →

Recent activity from admiralmetabolic and ggsurvfit

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

  1. 20d agoggsurvfitGray-test p-values matched to the plotted outcome by name
  2. 6mo agoadmiralmetabolicTemplate path and CRAN fixes, plus an Ask AI docs widget
  3. 10mo agoggsurvfitggplot2 v4.0.0 compatibility and multi-state CI label fix
  4. 1y agoadmiralmetabolicADLB template and metabolic lab datasets
  5. 1y agoadmiralmetabolicInitial release with waist-ratio derivations for obesity
  6. 2y agoggsurvfitNegative follow-up times and a cloglog transformation
  7. 2y agoggsurvfitAesthetic defaults become switchable and alignment is exported
  8. 2y agoggsurvfitConfidence limits corrected for monotonicity-reversing transforms
  9. 3y agoggsurvfitGlue syntax in risk tables and coxph model support

Frequently asked questions

What is the difference between admiralmetabolic and ggsurvfit?

They serve adjacent needs but don't currently overlap on shipped themes. ggsurvfit is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is admiralmetabolic better than ggsurvfit?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggsurvfit is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to admiralmetabolic?

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

What are the best alternatives to ggsurvfit?

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