cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
A side-by-side editorial comparison of dcurves and epidict — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A spin-out dictionary reader for MSF epidemiological data, finding its shape on CRAN
epidict reads and applies the data dictionaries MSF field epidemiologists use to standardise outbreak and survey datasets. It was split out of the larger sitrep toolchain so the dictionary-reading and variable-renaming functions could ship on CRAN independently. Three releases in roughly two months have taken it from that initial separation to handling intersectional dictionaries.
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.
epidict reads and applies the data dictionaries MSF field epidemiologists use to standardise outbreak and survey datasets. It was split out of the larger sitrep toolchain so the dictionary-reading and variable-renaming functions could ship on CRAN independently. Three releases in roughly two months have taken it from that initial separation to handling intersectional dictionaries.
The arc is a package being unbundled and then reassembled as its dependencies land on CRAN. The 0.1.0 release deliberately dropped msf_dict_rename_helper() because its dependencies weren't available; 0.2.0 put it back. 0.3.0 is the first release that adds rather than restores, extending intersectional dictionary support and giving callers control over name cleaning.
Expect the next releases to keep widening dictionary coverage rather than changing the API, since the reinstatement work that dominated 0.1.0 to 0.2.0 is now finished.
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 dcurves or epidict.
A choice-based IRT model published once in 2019 and kept compiling ever since
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
See all dcurves alternatives → · See all epidict alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. dcurves and epidict 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. dcurves and epidict 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 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.
Top epidict alternatives in Analytics are ranked by recent ship velocity. Browse the "epidict alternatives" section above for the current picks, or visit /alternatives/epidict for the full list with editorial commentary on each.