secuTrialR
A Swiss clinical-trial data reader that surfaces once every couple of years to clear check notes.
A side-by-side editorial comparison of edibble and rrum — release velocity, themes, recent moves, and the top alternatives to consider.
A grammar for experimental design that learned to compose designs and track its own provenance.
edibble expresses experimental designs declaratively — units, treatments, records and their allotments — rather than calling a canned design function. Since 1.0.0 its internals run on a Provenance object that records the commands used to build a design, and 1.1.0 added conditional treatments, design composition and a separated simulation step. Recent work has focused on designs constructed from existing data rather than from scratch.
Six years past its API cleanup, rrum ships only what the compiler demands.
rrum estimates the reduced Reparameterized Unified Model via a Gibbs sampler in Rcpp/Armadillo, with simulation delegated to its sibling package simcdm. The user-facing API has been settled since 2019, when the entry point was renamed and simulation was moved out. Releases since then have been build and CRAN compliance work.
edibble expresses experimental designs declaratively — units, treatments, records and their allotments — rather than calling a canned design function. Since 1.0.0 its internals run on a Provenance object that records the commands used to build a design, and 1.1.0 added conditional treatments, design composition and a separated simulation step. Recent work has focused on designs constructed from existing data rather than from scratch.
Development has moved from vocabulary to composition. Early releases established the core grammar; 1.0.0 replaced the internal R6 machinery with a Provenance object that tracks both internal and external commands, which is what lets a design carry its own construction history. On that foundation 1.1.0 added the ability to add two designs together, express conditional treatment structures, and split simulation specification from execution. The 2025 release turns toward a different entry point — wiring up level edges and unit attributes when an edibble object is built from data that already exists, rather than from a design declared up front.
Expect continued work on designs derived from existing data, since that is where the last release concentrated and it is the path least covered by the declarative grammar.
rrum estimates the reduced Reparameterized Unified Model via a Gibbs sampler in Rcpp/Armadillo, with simulation delegated to its sibling package simcdm. The user-facing API has been settled since 2019, when the entry point was renamed and simulation was moved out. Releases since then have been build and CRAN compliance work.
The arc runs from an API-breaking consolidation in 2019, through a 2023 release fixing C++ deprecations and adding a pkgdown site, to a 2025 maintenance release that raises dependency floors and swaps a deprecated Armadillo conversion call. Each release is triggered by something outside the package — R-devel, CRAN check notes, an Armadillo deprecation — rather than by modeling work. The 2025 release arrived the same morning as a near-identical one for edina, marking it as a maintainer-wide sweep across the lab's packages.
The next release will most likely be another externally forced compatibility fix, since three consecutive releases have been reactions to toolchain deprecations rather than to user requests.
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 edibble or rrum.
A Swiss clinical-trial data reader that surfaces once every couple of years to clear check notes.
Brazil's flight-data package keeps working around what ANAC publishes and when.
A star-schema modelling package grew a query language, a deployment path, and then a map layer.
A water-research lab's ODBC helper, still fighting Windows database drivers a decade in.
PACTA's loan-book matcher opened up to sector taxonomies other than its own.
PACTA's climate-alignment charting layer split prep from plotting, then settled into stable.
See all edibble alternatives → · See all rrum alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. edibble and rrum 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. edibble and rrum 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 edibble alternatives in Analytics are ranked by recent ship velocity. Browse the "edibble alternatives" section above for the current picks, or visit /alternatives/edibble for the full list with editorial commentary on each.
Top rrum alternatives in Analytics are ranked by recent ship velocity. Browse the "rrum alternatives" section above for the current picks, or visit /alternatives/rrum for the full list with editorial commentary on each.