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posteriordb vs simtrial

A side-by-side editorial comparison of posteriordb and simtrial — release velocity, themes, recent moves, and the top alternatives to consider.

posteriordb vs simtrial: at a glance

Featureposteriordbsimtrial
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesbayesian, benchmarking, reference-data, stanclinical-trials, group-sequential, survival-analysis, simulation
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is posteriordb?

A reference posterior database that hit 1.0 with a paper, and is now graded on the statistics it ships.

posteriordb distributes Bayesian models with data and reference posterior draws so inference algorithms can be benchmarked against a common target. It reached 1.0.0 alongside a published paper, and ships both R and Python access. Recent work is about the metadata around the draws — licences, machine-readable dataset descriptors, and additional summary statistics.

Read the full posteriordb trajectory →

What is simtrial?

A fixed-design trial simulator grew a pluggable test framework, then spent a year proving the numbers

simtrial simulates time-to-event clinical trials and applies the tests used to analyse them — logrank, weighted logrank, MaxCombo, RMST, milestone. The 0.4.0 release turned it from a fixed-sample simulator into a group sequential one and standardised every test behind a common output contract, and the releases since have been about making that machinery correct and fast enough to run at scale. Version 1.0.0 arrived in June 2025 with the API settled and three vignettes explaining both the one-call and build-it-yourself paths.

Read the full simtrial trajectory →

posteriordb vs simtrial: editorial side-by-side

P
posteriordb
ANALYTICS
0.0

A reference posterior database that hit 1.0 with a paper, and is now graded on the statistics it ships.

◆ Current state

posteriordb distributes Bayesian models with data and reference posterior draws so inference algorithms can be benchmarked against a common target. It reached 1.0.0 alongside a published paper, and ships both R and Python access. Recent work is about the metadata around the draws — licences, machine-readable dataset descriptors, and additional summary statistics.

◆ Where it's heading

The database is maturing from a model collection into a citable benchmark asset: licence information per model, a Croissant metadata file for dataset discovery, and summary statistics like mean squared value and lag-1 autocorrelation that let users judge whether reference draws are good enough for their comparison. Earlier releases were about content and correctness; current ones are about making the content machine-readable and verifiable.

◆ Prediction

Further work should continue on draw-quality diagnostics and metadata rather than model count, since the last two releases both added ways to assess the reference draws instead of adding posteriors.

S
simtrial
ANALYTICS
0.0

A fixed-design trial simulator grew a pluggable test framework, then spent a year proving the numbers

◆ Current state

simtrial simulates time-to-event clinical trials and applies the tests used to analyse them — logrank, weighted logrank, MaxCombo, RMST, milestone. The 0.4.0 release turned it from a fixed-sample simulator into a group sequential one and standardised every test behind a common output contract, and the releases since have been about making that machinery correct and fast enough to run at scale. Version 1.0.0 arrived in June 2025 with the API settled and three vignettes explaining both the one-call and build-it-yourself paths.

◆ Where it's heading

Post-1.0 the work is almost entirely statistical correctness and speed, and it is concentrated in sim_gs_n(): one-sided efficacy bounds, stratified targeted-event cut dates, a helper that derives cuttings straight from the design object. Performance moves in one direction throughout — dplyr replaced by data.table, foreach combination replaced by manual assembly, parallelisation added to sim_fixed_n() — because simulation-based operating characteristics are only useful if you can afford enough replications.

◆ Prediction

The recent fixes cluster on stratified and group sequential paths, so the next release most likely continues there rather than adding a new test type. The cut_from_design() helper suggests tighter coupling to gsDesign2 design objects is the direction of travel.

Alternatives to posteriordb and simtrial

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 posteriordb or simtrial.

See all posteriordb alternatives → · See all simtrial alternatives →

Recent activity from posteriordb and simtrial

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 8mo agosimtrialOne-sided efficacy bound and stratified cut date corrected
  2. 11mo agosimtrialsim_gs_n moved to data.table; stratified design example added
  3. 1y agosimtrial1.0.0 settles the wlr interface and documents both simulation paths
  4. 1y agoposteriordb1.0.0: licences, Croissant metadata, and draw diagnostics
  5. 1y agosimtrialMilestone Z-score denominator corrected; parallel sim_fixed_n arrives
  6. 2y agosimtrialChecks pass without Suggests dependencies
  7. 2y agosimtrialRMST and milestone tests, plus a user-definable cut and test framework
  8. 2y agoposteriordbStan code updated to 2.26 syntax; posterior tags cleaned
  9. 3y agoposteriordbNew posteriors and a corrected dogs model
  10. 5y agoposteriordbPython module gains GitHub-backed and env-var database paths

Frequently asked questions

What is the difference between posteriordb and simtrial?

They serve adjacent needs but don't currently overlap on shipped themes. posteriordb and simtrial 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 posteriordb better than simtrial?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. posteriordb and simtrial 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 posteriordb?

Top posteriordb alternatives in Analytics are ranked by recent ship velocity. Browse the "posteriordb alternatives" section above for the current picks, or visit /alternatives/posteriordb for the full list with editorial commentary on each.

What are the best alternatives to simtrial?

Top simtrial alternatives in Analytics are ranked by recent ship velocity. Browse the "simtrial alternatives" section above for the current picks, or visit /alternatives/simtrial for the full list with editorial commentary on each.