cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
A side-by-side editorial comparison of epidict and fmtr — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Rebuilding SAS's formatting layer in R, one format specification at a time
fmtr applies formats to R data the way SAS applies them: named format catalogues, format lists, and an fapply() that maps a specification onto a vector. It is part of a family of packages that reconstruct SAS reporting idioms in R, and it shares infrastructure with them — labels.data.frame() was moved out to the common package, which fmtr now depends on. The recent releases have been closing specific gaps against SAS's own format vocabulary.
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.
fmtr applies formats to R data the way SAS applies them: named format catalogues, format lists, and an fapply() that maps a specification onto a vector. It is part of a family of packages that reconstruct SAS reporting idioms in R, and it shares infrastructure with them — labels.data.frame() was moved out to the common package, which fmtr now depends on. The recent releases have been closing specific gaps against SAS's own format vocabulary.
The direction is parity, pursued in small increments. Quarter format codes were added because base R has none; the SAS best. format was reimplemented, then hardened against the variations people actually write; statistical summary helpers like fmt_mean_sd() and fmt_mean_stderr() cover the cell contents clinical tables need. The structural work is largely behind it, including the breaking 2022 move that handed labelling to a sibling package, so what remains is vocabulary coverage.
The pattern of adding a SAS format, then a release to handle its variants, suggests the next releases continue filling in format codes and summary helpers rather than changing how formats are applied.
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 epidict or fmtr.
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
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
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
See all epidict alternatives → · See all fmtr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. epidict and fmtr 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. epidict and fmtr 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 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.
Top fmtr alternatives in Analytics are ranked by recent ship velocity. Browse the "fmtr alternatives" section above for the current picks, or visit /alternatives/fmtr for the full list with editorial commentary on each.