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Comparison · Infra & APIs
adjustedCurves vs ggInterval
A side-by-side editorial comparison of adjustedCurves and ggInterval — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
adjustedCurves vs ggInterval: at a glance
What is adjustedCurves?
A survival curve package spending release after release correcting its own estimates
adjustedCurves computes confounder-adjusted survival and cumulative incidence curves across a range of estimators - IPTW, AIPTW, Aalen-Johansen, direct standardisation - with support for multiple imputation and bootstrapping. The recent releases are dominated by corrections to numbers the package already reported. Version 0.11.4 fixed cumulative incidence estimates under method="aalen_johansen" that were being read one time step early, which the maintainer notes could differ substantially when events are few, and added risk and event counts to the ggsurvplot conversion including correctly pooled values under multiple imputation.
What is ggInterval?
Interval-valued data plotting, spending 2026 making its function names and examples survive CRAN.
ggInterval visualizes symbolic interval-valued data — observations recorded as ranges rather than points — with a family of plot functions in the ggplot2 idiom. The plot catalogue grew most recently with interval correlation heatmaps and interval line plots compatible with time-series input. The three releases before that were corrections: seven plot functions renamed for consistency, examples switched from dontrun to donttest at CRAN's request, and a vignette rewritten to demonstrate every function in one place.
adjustedCurves vs ggInterval: editorial side-by-side
adjustedCurves
0.0INFRA · APIS
A survival curve package spending release after release correcting its own estimates
◆ Current state
adjustedCurves computes confounder-adjusted survival and cumulative incidence curves across a range of estimators - IPTW, AIPTW, Aalen-Johansen, direct standardisation - with support for multiple imputation and bootstrapping. The recent releases are dominated by corrections to numbers the package already reported. Version 0.11.4 fixed cumulative incidence estimates under method="aalen_johansen" that were being read one time step early, which the maintainer notes could differ substantially when events are few, and added risk and event counts to the ggsurvplot conversion including correctly pooled values under multiple imputation.
◆ Where it's heading
Multiple imputation is the recurring fault line. The standard error pooling formula was implemented incorrectly until 0.11.2, then fixed again in 0.11.3 for the bootstrapping-plus-imputation combination, and 0.11.4 added the pooled risk table values that had previously been omitted entirely. A separate thread quietly removed capability: tmle and ostmle methods went in 0.10.0, and tmle support was pulled again in 0.11.1 after the concrete package left CRAN. Feature work does happen - risk tables, contrast arguments, the extend_to_last control on IPTW curves - but it is outweighed by correction.
◆ Prediction
Expect continued estimator-level corrections rather than new methods, and a possible return of tmle support if its upstream dependency returns to CRAN, since the removal was described as temporary.
ggInterval
0.0INFRA · APIS
Interval-valued data plotting, spending 2026 making its function names and examples survive CRAN.
◆ Current state
ggInterval visualizes symbolic interval-valued data — observations recorded as ranges rather than points — with a family of plot functions in the ggplot2 idiom. The plot catalogue grew most recently with interval correlation heatmaps and interval line plots compatible with time-series input. The three releases before that were corrections: seven plot functions renamed for consistency, examples switched from dontrun to donttest at CRAN's request, and a vignette rewritten to demonstrate every function in one place.
◆ Where it's heading
The package is consolidating an interface that had drifted. Renaming seven functions in a single release is the clearest signal — the naming was inconsistent enough to be worth breaking, and the vignette rewrite that followed suggests discoverability was the underlying complaint. Underneath that, the additions are steady and narrow: each release brings interval-aware versions of plot types that already exist for point data, which is the whole premise of the package.
◆ Prediction
The pattern of porting one more standard plot type into interval-aware form each release is the most likely continuation; the tsplot compatibility in the latest version hints that time-series interval data is the direction attracting attention.
Alternatives to adjustedCurves and ggInterval
Other Infra & APIs 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 adjustedCurves or ggInterval.
WPML
WPML made machine translation the default, and its point releases keep chasing WordPress and page builders.
forestploter
A forest plot package that keeps handing users control of one more graphical detail.
rgm
A microbiome network model that got itself un-archived by deleting the dependency that killed it.
contagionchannels
Three releases in ten days, every one of them a CRAN reviewer's correction rather than a code change.
tidyaudit
Pipeline provenance for tidyverse workflows, recording what changed at each step without keeping the data.
See all adjustedCurves alternatives → · See all ggInterval alternatives →
Recent activity from adjustedCurves and ggInterval
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agoggIntervalInterval correlation heatmaps and time-series-compatible line plots
- 6mo agoggIntervalExamples switched to donttest per CRAN review
- 6mo agoggIntervalVignette rewritten to cover every plot function
- 6mo agoggIntervalSeven plot functions renamed for consistency
- 6mo agoadjustedCurvesOff-by-one-step error corrected in cumulative incidence estimates
- 1y agoadjustedCurvesIPTW curves can now extend to the last observed time
- 2y agoadjustedCurvesDropped arguments and a wrong multiple-imputation pooling formula
- 2y agoadjustedCurvesRisk tables, contrast consolidation and faster bootstrapping
- 3y agoadjustedCurvestmle and ostmle methods dropped
- 3y agoadjustedCurvesDependency compatibility and installation documentation
Frequently asked questions
What is the difference between adjustedCurves and ggInterval?
Both compete on the same themes — r-package — within Infra & APIs. adjustedCurves and ggInterval 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 adjustedCurves better than ggInterval?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. adjustedCurves and ggInterval 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 Infra & APIs products to evaluate alongside.
What are the best alternatives to adjustedCurves?
Top adjustedCurves alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "adjustedCurves alternatives" section above for the current picks, or visit /alternatives/adjustedcurves for the full list with editorial commentary on each.
What are the best alternatives to ggInterval?
Top ggInterval alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggInterval alternatives" section above for the current picks, or visit /alternatives/gginterval for the full list with editorial commentary on each.