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Comparison · Infra & APIs

adjustedCurves vs estimatr

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

Shared themes:causal-inferencer-package

adjustedCurves vs estimatr: at a glance

FeatureadjustedCurvesestimatr
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themessurvival-analysis, causal-inference, r-package, biostatisticscausal-inference, experiments, robust-standard-errors, econometrics
Last editorial update1h ago30m ago
WebsiteVisit →Visit →

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.

Read the full adjustedCurves trajectory →

What is estimatr?

Fast design-based estimators for experiments, coasting on CRAN patches.

estimatr provides the design-based regression estimators the DeclareDesign ecosystem is built on — robust and cluster-robust standard errors, blocked and clustered randomization inference — implemented for speed rather than generality. The last three releases carry no substantive notes: each is a merge commit for a CRAN patch, one of them accompanied by a typo fix.

Read the full estimatr trajectory →

adjustedCurves vs estimatr: editorial side-by-side

A
adjustedCurves
INFRA · APIS
0.0

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.

E
estimatr
INFRA · APIS
0.0

Fast design-based estimators for experiments, coasting on CRAN patches.

◆ Current state

estimatr provides the design-based regression estimators the DeclareDesign ecosystem is built on — robust and cluster-robust standard errors, blocked and clustered randomization inference — implemented for speed rather than generality. The last three releases carry no substantive notes: each is a merge commit for a CRAN patch, one of them accompanied by a typo fix.

◆ Where it's heading

Direction cannot be read from this feed. The release notes are unedited merge-commit messages, so the only signal is cadence — roughly annual, each release framed as a CRAN patch rather than as feature work. That pattern is consistent with a package whose estimators are considered finished and which now moves only when CRAN policy requires it.

◆ Prediction

On the evidence here the next release is another CRAN compliance patch, but the notes are too thin to support a confident read of what the maintainers are actually working on.

Alternatives to adjustedCurves and estimatr

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 estimatr.

See all adjustedCurves alternatives → · See all estimatr alternatives →

Recent activity from adjustedCurves and estimatr

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

  1. 6mo agoadjustedCurvesOff-by-one-step error corrected in cumulative incidence estimates
  2. 1y agoadjustedCurvesIPTW curves can now extend to the last observed time
  3. 1y agoestimatrCRAN version 1.0.4
  4. 2y agoadjustedCurvesDropped arguments and a wrong multiple-imputation pooling formula
  5. 2y agoadjustedCurvesRisk tables, contrast consolidation and faster bootstrapping
  6. 2y agoestimatrCRAN version 1.0.2
  7. 3y agoestimatrCRAN version 1.0.0
  8. 3y agoadjustedCurvestmle and ostmle methods dropped
  9. 3y agoadjustedCurvesDependency compatibility and installation documentation

Frequently asked questions

What is the difference between adjustedCurves and estimatr?

Both compete on the same themes — causal-inference, r-package — within Infra & APIs. adjustedCurves and estimatr 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 estimatr?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. adjustedCurves and estimatr 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 estimatr?

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