MetaboAnalystR
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
A side-by-side editorial comparison of cIRT and dcurves — release velocity, themes, recent moves, and the top alternatives to consider.
A choice-based IRT model published once in 2019 and kept compiling ever since
cIRT implements Choice Item Response Theory, jointly modelling which item a respondent picks and how they perform on it — the setting where subjects choose between a harder and an easier question and the choice itself carries information. It comes out of the TMSA Lab, is built on Rcpp and RcppArmadillo, and has had one substantive release since reaching CRAN. Everything after early 2019 is build-system and toolchain upkeep.
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
dcurves implements decision curve analysis — evaluating a prediction model or diagnostic test by net benefit across the range of thresholds a clinician might plausibly use, rather than by a single discrimination statistic. Its API stabilised in 2022 around dca() and test_consequences(). The two releases since exist because gtsummary and CRAN documentation rules changed, not because the method did.
cIRT implements Choice Item Response Theory, jointly modelling which item a respondent picks and how they perform on it — the setting where subjects choose between a harder and an easier question and the choice itself carries information. It comes out of the TMSA Lab, is built on Rcpp and RcppArmadillo, and has had one substantive release since reaching CRAN. Everything after early 2019 is build-system and toolchain upkeep.
The package's whole functional history fits in a two-day window in January 2019, when the CRAN release and its immediate follow-ups were tagged in one batch, followed a day later by a release enabling C++11 and OpenMP and fixing the choice generation procedure. Since then the releases track other people's deprecations: Armadillo dropping conversions, RcppArmadillo requiring a different Makevars, R raising its floor. The 2025 release is entirely of that kind, down to swapping the README to Quarto.
The dependency floors were just raised to current Rcpp and RcppArmadillo, so the next release is most likely the one after Armadillo deprecates something else.
dcurves implements decision curve analysis — evaluating a prediction model or diagnostic test by net benefit across the range of thresholds a clinician might plausibly use, rather than by a single discrimination statistic. Its API stabilised in 2022 around dca() and test_consequences(). The two releases since exist because gtsummary and CRAN documentation rules changed, not because the method did.
The package reached its intended scope quickly and then stopped. Its 2022 releases did the substantive work: adding threshold-level diagnostic accuracy, tightening argument validation, and taking one breaking change to make net-interventions-avoided plots show the treat-all and treat-none reference lines by default. Since then it has moved only as a dependent of the wider tidy-modelling documentation ecosystem it plugs into.
Nothing in these entries points to method or API work; expect the next release to be another compatibility or CRAN documentation patch.
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 cIRT or dcurves.
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
Rebuilding SAS's formatting layer in R, one format specification at a time
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
Stream-network spatial models learning to run on data that no longer fits in memory
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
The config-authoring half of hubverse, pinned to whatever the schema is doing this quarter
See all cIRT alternatives → · See all dcurves alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. cIRT and dcurves 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cIRT and dcurves 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 Analytics products to evaluate alongside.
Top cIRT alternatives in Analytics are ranked by recent ship velocity. Browse the "cIRT alternatives" section above for the current picks, or visit /alternatives/cirt for the full list with editorial commentary on each.
Top dcurves alternatives in Analytics are ranked by recent ship velocity. Browse the "dcurves alternatives" section above for the current picks, or visit /alternatives/dcurves for the full list with editorial commentary on each.