cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
Comparison · Analytics
TrialEmulation vs tulpaRatio
A side-by-side editorial comparison of TrialEmulation and tulpaRatio — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
TrialEmulation vs tulpaRatio: at a glance
What is TrialEmulation?
Target trial emulation held steady by dependency maintenance, not new methods.
TrialEmulation implements target trial emulation from observational data, using duckdb to handle the expanded per-period datasets that approach generates. Every release in the visible window is upkeep: two consecutive releases removing the archived parglm dependency, two fixing tests against testthat updates, and two tracking duckdb sampling changes. No methodological work appears in the feed since before February 2025.
What is tulpaRatio?
A Bayesian ratio-modelling package that threw out its Stan dependency and wrote its own sampler
ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.
TrialEmulation vs tulpaRatio: editorial side-by-side
TrialEmulation
0.0ANALYTICS
Target trial emulation held steady by dependency maintenance, not new methods.
◆ Current state
TrialEmulation implements target trial emulation from observational data, using duckdb to handle the expanded per-period datasets that approach generates. Every release in the visible window is upkeep: two consecutive releases removing the archived parglm dependency, two fixing tests against testthat updates, and two tracking duckdb sampling changes. No methodological work appears in the feed since before February 2025.
◆ Where it's heading
The package is being kept installable rather than extended. Its dependency surface, duckdb for storage, parglm for fitting, testthat for checks, generates most of the release traffic, and CRAN archiving parglm forced two separate releases three months apart to fully excise it. The version numbering, still in the 0.0.4.x range after years, suggests the maintainers do not consider the API settled enough to promote.
◆ Prediction
Further releases will most likely be triggered by upstream dependency changes; the entries give no signal on when methodological work resumes.
tulpaRatio
0.0ANALYTICS
A Bayesian ratio-modelling package that threw out its Stan dependency and wrote its own sampler
◆ Current state
ratiod models ratios, rates and proportions hierarchically, with the stated position that a ratio is a derived quantity and inference should run on the latent numerator and denominator processes rather than their quotient. The 1.0.0 release shipped a native HMC/NUTS backend, removing the Stan dependency that packages in this space normally take as given. Everything since has been sampler optimisation, benchmarked against the Stan implementations it replaced.
◆ Where it's heading
The feed reads as one architectural bet followed by the work to justify it. After the native backend landed, the releases are a steady march of gradient and adaptation work — hand-coded gradients for more model families, L-BFGS mass matrix adaptation, an O2 build — each measured as a speed multiple against Stan. Coverage is tracked openly as a fraction (48 of 60 hand-coded configs), and unresolved problems are named rather than buried, including a deferred GP spatial bug.
◆ Prediction
The hand-coded gradient coverage count is the visible backlog, so the next releases most likely close the remaining configs and resolve the GP spatial issue that the benchmark release explicitly deferred.
Alternatives to TrialEmulation and tulpaRatio
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 TrialEmulation or tulpaRatio.
MetaboAnalystR
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
fmtr
Rebuilding SAS's formatting layer in R, one format specification at a time
betaselectr
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
SSN2
Stream-network spatial models learning to run on data that no longer fits in memory
BiocManager
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
See all TrialEmulation alternatives → · See all tulpaRatio alternatives →
Recent activity from TrialEmulation and tulpaRatio
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agoTrialEmulationDocumentation references to the archived parglm removed
- 6mo agotulpaRatioHand-coded gradients reach binomial zero-inflated and hurdle models
- 6mo agotulpaRatioGaussian process sampling reaches roughly 4x Stan
- 7mo agotulpaRatioL-BFGS mass matrix adaptation for MSGP models
- 7mo agotulpaRatioBenchmarks published for 35 of 40 model configurations
- 7mo agoTrialEmulationparglm dependency dropped after CRAN archiving
- 7mo agotulpaRatioFirst stable release ships a native HMC/NUTS backend, no Stan required ⚡
- 9mo agoTrialEmulationTest fixes for updated testthat, plus link updates
- 9mo agoTrialEmulationCompatibility fixes ahead of testthat 3.3.0
- 1y agoTrialEmulationTests updated for duckdb 1.3.0 sampling; R 4.1 now required
- 1y agoTrialEmulationTests updated for duckdb 1.2.0 sampling changes
Frequently asked questions
What is the difference between TrialEmulation and tulpaRatio?
Both compete on the same themes — r-package — within Analytics. TrialEmulation and tulpaRatio 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 TrialEmulation better than tulpaRatio?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. TrialEmulation and tulpaRatio 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 TrialEmulation?
Top TrialEmulation alternatives in Analytics are ranked by recent ship velocity. Browse the "TrialEmulation alternatives" section above for the current picks, or visit /alternatives/trialemulation for the full list with editorial commentary on each.
What are the best alternatives to tulpaRatio?
Top tulpaRatio alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpaRatio alternatives" section above for the current picks, or visit /alternatives/tulparatio for the full list with editorial commentary on each.