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Comparison · Infra & APIs

adjustedCurves vs dqcheckr

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

Shared themes:r-package

adjustedCurves vs dqcheckr: at a glance

FeatureadjustedCurvesdqcheckr
SectorInfra & APIsInfra & APIs
Velocity score0.02.5
Sparks · 30d00
Top themessurvival-analysis, causal-inference, r-package, biostatisticsdata-quality, duckdb, drift-analysis, yaml-config
Last editorial update1d ago1h 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 dqcheckr?

dqcheckr adds drift analysis, then removes the YAML a user had to hand-write.

dqcheckr runs configurable data-quality checks over files and DuckDB tables, driven by YAML dataset configs and recording results as snapshots. The 0.2.0 release added the ability to compare two historical snapshots and report per-column statistical drift, schema changes and trend charts, extending the tool from point-in-time checking into change over time. The most recent tag, 0.3.0, attacks the other friction point by generating the config itself from a sniff pass over the data.

Read the full dqcheckr trajectory →

adjustedCurves vs dqcheckr: 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.

D
dqcheckr
INFRA · APIS
2.5

dqcheckr adds drift analysis, then removes the YAML a user had to hand-write.

◆ Current state

dqcheckr runs configurable data-quality checks over files and DuckDB tables, driven by YAML dataset configs and recording results as snapshots. The 0.2.0 release added the ability to compare two historical snapshots and report per-column statistical drift, schema changes and trend charts, extending the tool from point-in-time checking into change over time. The most recent tag, 0.3.0, attacks the other friction point by generating the config itself from a sniff pass over the data.

◆ Where it's heading

Both moves point the same way: reduce what the operator has to write and know. Config generation removes the hand-authored YAML that gated first use, list_runs() and validate_config() make an existing setup inspectable, and the snapshot comparison turns accumulated run history into a second product surface. Check coverage keeps widening underneath — outlier detection, composite keys, row-count and file-size ceilings — and the reporting layer moved from rmarkdown to Quarto, with existing 0.1.x databases auto-migrated on first run.

◆ Prediction

Expect the generated configs and the drift reports to converge, so a sniffed config can seed thresholds from the snapshot history rather than from defaults, plus continued growth in the numbered QC check catalogue.

Alternatives to adjustedCurves and dqcheckr

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 dqcheckr.

See all adjustedCurves alternatives → · See all dqcheckr alternatives →

Recent activity from adjustedCurves and dqcheckr

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

  1. 24d agodqcheckrConfig generation from data sniffing; run listing added
  2. 2mo agodqcheckrDuckDB CSV ingestion fixed for undetectable delimiters
  3. 2mo agodqcheckrSnapshot drift analysis arrives; reports move to Quarto
  4. 6mo agoadjustedCurvesOff-by-one-step error corrected in cumulative incidence estimates
  5. 1y agoadjustedCurvesIPTW curves can now extend to the last observed time
  6. 2y agoadjustedCurvesDropped arguments and a wrong multiple-imputation pooling formula
  7. 2y agoadjustedCurvesRisk tables, contrast consolidation and faster bootstrapping
  8. 3y agoadjustedCurvestmle and ostmle methods dropped
  9. 3y agoadjustedCurvesDependency compatibility and installation documentation

Frequently asked questions

What is the difference between adjustedCurves and dqcheckr?

Both compete on the same themes — r-package — within Infra & APIs. dqcheckr 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 adjustedCurves better than dqcheckr?

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

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