tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of cfr and datasetjson — release velocity, themes, recent moves, and the top alternatives to consider.
cfr packaged delay-corrected severity estimation, then went quiet on maintenance.
The package estimates disease severity and case ascertainment while correcting for the delay between a case being reported and its outcome being known. After the 0.1.1 rework of the estimation internals and a maintainer handover to Adam Kucharski, activity dropped to a vignette and an R-devel compatibility patch in February 2025.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
The package estimates disease severity and case ascertainment while correcting for the delay between a case being reported and its outcome being known. After the 0.1.1 rework of the estimation internals and a maintainer handover to Adam Kucharski, activity dropped to a vignette and an R-devel compatibility patch in February 2025.
The methodological work is done and consolidated: likelihood approximation is now selected automatically from outbreak size and an initial severity estimate, and the internals were renamed with a dot prefix to close the public surface down to cfr_static(), cfr_rolling() and the data-preparation generic. Releases since have been documentation and compatibility only.
The 0.1.0 notes flagged time-varying ascertainment as future work and it has not appeared in the two releases since; nothing in these entries indicates when or whether it lands.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
The package's roadmap is not its own — it tracks a CDISC standard that is still moving, and 0.3.0 is what happens when the standard revises: object model, read and write paths, and JSON backend all changed together. Performance was addressed in the same pass, which matters because submission datasets are large enough that a slow serialiser is a real constraint.
The next significant release will most likely follow the next Dataset-JSON schema revision rather than an internal roadmap, given that 0.3.0 was driven entirely by the 1.1.0 update.
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 cfr or datasetjson.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all cfr alternatives → · See all datasetjson alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. cfr and datasetjson 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. cfr and datasetjson 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 cfr alternatives in Analytics are ranked by recent ship velocity. Browse the "cfr alternatives" section above for the current picks, or visit /alternatives/cfr for the full list with editorial commentary on each.
Top datasetjson alternatives in Analytics are ranked by recent ship velocity. Browse the "datasetjson alternatives" section above for the current picks, or visit /alternatives/datasetjson for the full list with editorial commentary on each.