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Comparison · Infra & APIs
adjustedCurves vs sps
A side-by-side editorial comparison of adjustedCurves and sps — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
adjustedCurves vs sps: 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 sps?
sps keeps sanding down sequential Poisson sampling rather than adding to it.
The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.
adjustedCurves vs sps: 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.
sps
2.5INFRA · APIS
sps keeps sanding down sequential Poisson sampling rather than adding to it.
◆ Current state
The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.
◆ Where it's heading
Development is consolidation rather than expansion. Most releases either speed up an existing routine or remove a decision the user previously had to make by hand, such as picking the smallest parameter that keeps replicate weights non-negative. Documentation and tooling get comparable attention to the algorithms, with a dedicated vignette on inclusion probabilities and a recent switch of test and documentation infrastructure. The API surface has been essentially stable across the window.
◆ Prediction
Expect continued small ergonomic and performance releases against the existing function set rather than new sampling designs, which is the pattern every release in this window follows.
Alternatives to adjustedCurves and sps
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 sps.
daedalus
An epidemic-economic model teaching its interventions to react to the outbreak itself.
bkmrhat
A parallel-chain helper for bkmr that has settled into pure upkeep.
driveR
A cancer driver prioritization package that ships rarely and mostly to stay installable
metR
A meteorology ggplot2 extension where the netCDF reader became the main event
IsoriX
An isotope geolocation package still recovering from the r-spatial retirement
See all adjustedCurves alternatives → · See all sps alternatives →
Recent activity from adjustedCurves and sps
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agospsDocumentation polish; switches to tinytest and litedown
- 6mo agoadjustedCurvesOff-by-one-step error corrected in cumulative incidence estimates
- 9mo agospsFixes extra argument handling in sps_iterator()
- 11mo agospsAdds divisor_method() and a one-unit-at-a-time sampling iterator
- 1y agoadjustedCurvesIPTW curves can now extend to the last observed time
- 1y agospsAdds an inclusion-probability vignette and faster partial sorting
- 1y agospsAutomatic tau selection for replicate weights
- 2y agoadjustedCurvesDropped arguments and a wrong multiple-imputation pooling formula
- 2y agoadjustedCurvesRisk tables, contrast consolidation and faster bootstrapping
- 2y agospsAdds becomes_ta() for take-all stratum sample sizes
- 3y agoadjustedCurvestmle and ostmle methods dropped
- 3y agoadjustedCurvesDependency compatibility and installation documentation
Frequently asked questions
What is the difference between adjustedCurves and sps?
Both compete on the same themes — r-package — within Infra & APIs. sps 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 sps?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. sps 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 sps?
Top sps alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "sps alternatives" section above for the current picks, or visit /alternatives/sps for the full list with editorial commentary on each.