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datasetjson vs ggsurvfit

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

Shared themes:cdisc

datasetjson vs ggsurvfit: at a glance

Featuredatasetjsonggsurvfit
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesclinical-data, cdisc, json, r-packagesurvival-analysis, ggplot2, competing-risks, clinical-plots
Last editorial update1h ago7h ago
WebsiteVisit →Visit →

What is datasetjson?

datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.

datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.

Read the full datasetjson 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 →

datasetjson vs ggsurvfit: editorial side-by-side

D
datasetjson
ANALYTICS
0.0

datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.

◆ Current state

datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.

◆ Where it's heading

The package's roadmap is not its own — it tracks a CDISC standard that is still moving, and 0.3.0 is what happens when the standard revises: object model, read and write paths, and JSON backend all changed together. Performance was addressed in the same pass, which matters because submission datasets are large enough that a slow serialiser is a real constraint.

◆ Prediction

The next significant release will most likely follow the next Dataset-JSON schema revision rather than an internal roadmap, given that 0.3.0 was driven entirely by the 1.1.0 update.

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 datasetjson 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 datasetjson or ggsurvfit.

See all datasetjson alternatives → · See all ggsurvfit alternatives →

Recent activity from datasetjson and ggsurvfit

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

  1. 21d agoggsurvfitGray-test p-values matched to the plotted outcome by name
  2. 10mo agoggsurvfitggplot2 v4.0.0 compatibility and multi-state CI label fix
  3. 1y agodatasetjsonDataset-JSON 1.1.0 support with a redesigned object model
  4. 2y agoggsurvfitNegative follow-up times and a cloglog transformation
  5. 2y agoggsurvfitAesthetic defaults become switchable and alignment is exported
  6. 2y agodatasetjsonReads and validates Dataset-JSON from URLs
  7. 2y agodatasetjsonInitial CRAN release
  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 datasetjson and ggsurvfit?

Both compete on the same themes — cdisc — within Analytics. 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 datasetjson 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 datasetjson?

Top datasetjson alternatives in Analytics are ranked by recent ship velocity. Browse the "datasetjson alternatives" section above for the current picks, or visit /alternatives/datasetjson 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.