tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
RBesT vs Tplyr
A side-by-side editorial comparison of RBesT and Tplyr — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:clinical-trials
RBesT vs Tplyr: at a glance
What is RBesT?
RBesT is teaching its Bayesian decision rules to answer two-sided questions.
RBesT builds meta-analytic-predictive priors — the machinery for borrowing historical control data into a new trial — and evaluates the operating characteristics of decisions made with them. The stable line has spent several releases on effective sample size: ESS for normal mixtures via a new `family` argument, boundary corrections when no responses or no non-responses are observed, and stabilised ELIR computations. The 1.9-0 release candidate extends the normal, binomial and Poisson outcome functions to two-sided decisions.
What is Tplyr?
Tplyr made clinical summary tables explain where every number came from.
Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.
RBesT vs Tplyr: editorial side-by-side
RBesT
0.0ANALYTICS
RBesT is teaching its Bayesian decision rules to answer two-sided questions.
◆ Current state
RBesT builds meta-analytic-predictive priors — the machinery for borrowing historical control data into a new trial — and evaluates the operating characteristics of decisions made with them. The stable line has spent several releases on effective sample size: ESS for normal mixtures via a new `family` argument, boundary corrections when no responses or no non-responses are observed, and stabilised ELIR computations. The 1.9-0 release candidate extends the normal, binomial and Poisson outcome functions to two-sided decisions.
◆ Where it's heading
Two currents run through the changelog. One is ESS hardening — nearly every release since 1.7-4 fixes another edge case where the ELIR calculation aborted or returned something unstable, which is what happens when a quantity used to justify prior strength to regulators gets scrutinised. The other is Stan and brms integration debt: array syntax updates, a minimum Stan version bump, truncated prior generation for `mixstanvar`, deterministic EM. The RC's contributor list shows a second active maintainer, and the work is broader than any recent stable release.
◆ Prediction
The release candidate covers all three outcome families and has already absorbed a round of review comments, so the next step is most likely the 1.9-0 CRAN release itself rather than further feature work.
Tplyr
0.0ANALYTICS
Tplyr made clinical summary tables explain where every number came from.
◆ Current state
Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.
◆ Where it's heading
Post-1.0 work has been about completing the metadata story and filling gaps in layer composition rather than adding table types — metadata for missing subjects, add_anti_join(), missing-subject rows, data limiting, and fixes to nested count layers where an inner value appears under several outer groups. Releases cluster tightly after a major version, then go quiet, and the window ends with a patch issued days after the release it corrects.
◆ Prediction
Further releases will most likely continue closing traceability and nested-layer edge cases rather than introducing new layer types, following the pattern of both post-1.0 feature releases.
Alternatives to RBesT and Tplyr
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 RBesT or Tplyr.
rlistings
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
datasetjson
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
Recent activity from RBesT and Tplyr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 5mo agoRBesTTwo-sided decisions across normal, binomial and Poisson outcomes ⚡
- 1y agoRBesTJSON read and write for mixture objects
- 1y agoRBesTess() fixed inside apply functions
- 1y agoRBesTESS for normal mixtures in the exponential family
- 1y agoRBesTTruncated mixture priors for brms, plus faster Stan models
- 2y agoTplyrMissing-subject metadata, add_anti_join(), and nested-layer fixes
- 2y agoRBesTStan array syntax update and CRAN system requirements
- 3y agoTplyrMetadata vignette fix and parenthesis hugging
- 3y agoTplyrDenominator logic fix ahead of CRAN release
- 3y agoTplyrReverse-dependency fix
- 3y agoTplyr1.0.0 introduces the traceability metadata framework ⚡
Frequently asked questions
What is the difference between RBesT and Tplyr?
Both compete on the same themes — clinical-trials — within Analytics. RBesT and Tplyr 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.
Is RBesT better than Tplyr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. RBesT and Tplyr 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.
What are the best alternatives to RBesT?
Top RBesT alternatives in Analytics are ranked by recent ship velocity. Browse the "RBesT alternatives" section above for the current picks, or visit /alternatives/rbest for the full list with editorial commentary on each.
What are the best alternatives to Tplyr?
Top Tplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "Tplyr alternatives" section above for the current picks, or visit /alternatives/tplyr for the full list with editorial commentary on each.