metatools
SDTM supplemental-qualifier merging got sturdier, then the package went quiet for two years.
Comparison · Analytics
ggsurvfit vs mlr3cmprsk
A side-by-side editorial comparison of ggsurvfit and mlr3cmprsk — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:survival-analysiscompeting-risks
ggsurvfit vs mlr3cmprsk: at a glance
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.
What is mlr3cmprsk?
Competing risks arrive in mlr3, going from a non-parametric baseline to Fine-Gray regression in seven weeks.
mlr3cmprsk extends mlr3 to competing-risks analysis: learners predicting cumulative incidence functions, plus measures to score them. It appeared in February 2026 and reached 0.0.5 by April, adding a Fine-Gray learner and a Brier score along the way. The version numbers say pre-release; the cadence says active build-out.
ggsurvfit vs mlr3cmprsk: editorial side-by-side
ggsurvfit
2.5ANALYTICS
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.
mlr3cmprsk
0.0ANALYTICS
Competing risks arrive in mlr3, going from a non-parametric baseline to Fine-Gray regression in seven weeks.
◆ Current state
mlr3cmprsk extends mlr3 to competing-risks analysis: learners predicting cumulative incidence functions, plus measures to score them. It appeared in February 2026 and reached 0.0.5 by April, adding a Fine-Gray learner and a Brier score along the way. The version numbers say pre-release; the cadence says active build-out.
◆ Where it's heading
The package assembled a working evaluation stack fast. It started with the Aalen-Johansen estimator as a non-parametric baseline, added Fine-Gray as a regression alternative, then filled in the scoring side with an AUC refactor and a fixed-time Brier score. Development has run in lockstep with survdistr and mlr3extralearners, which picked up the dependency at 1.5.2.
◆ Prediction
The visible gaps are more learners — cause-specific Cox and boosting variants — and the tuning and pipeline integration the rest of mlr3 expects; the measure side currently looks further along than the model side.
Alternatives to ggsurvfit and mlr3cmprsk
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 ggsurvfit or mlr3cmprsk.
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logrx
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See all ggsurvfit alternatives → · See all mlr3cmprsk alternatives →
Recent activity from ggsurvfit and mlr3cmprsk
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 20d agoggsurvfitGray-test p-values matched to the plotted outcome by name
- 4mo agomlr3cmprskBrier score for competing risks and an AUC refactor
- 4mo agomlr3cmprskFine-Gray learner brings regression modelling to competing risks ⚡
- 4mo agomlr3cmprskAalen-Johansen learner gains standard mlr3 properties
- 4mo agomlr3cmprskCIF interpolation pulled from survdistr
- 5mo agomlr3cmprskFirst release on mlr-org.r-universe
- 10mo agoggsurvfitggplot2 v4.0.0 compatibility and multi-state CI label fix
- 2y agoggsurvfitNegative follow-up times and a cloglog transformation
- 2y agoggsurvfitAesthetic defaults become switchable and alignment is exported
- 2y agoggsurvfitConfidence limits corrected for monotonicity-reversing transforms
- 3y agoggsurvfitGlue syntax in risk tables and coxph model support
Frequently asked questions
What is the difference between ggsurvfit and mlr3cmprsk?
Both compete on the same themes — survival-analysis, competing-risks — 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 ggsurvfit better than mlr3cmprsk?
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 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.
What are the best alternatives to mlr3cmprsk?
Top mlr3cmprsk alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3cmprsk alternatives" section above for the current picks, or visit /alternatives/mlr3cmprsk for the full list with editorial commentary on each.