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Comparison · Infra & APIs
BayesianMCPMod vs dataSDA
A side-by-side editorial comparison of BayesianMCPMod and dataSDA — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
BayesianMCPMod vs dataSDA: at a glance
What is BayesianMCPMod?
A Bayesian dose-finding package extends from continuous endpoints to binary ones
BayesianMCPMod implements the Bayesian form of MCP-Mod for dose-finding trials, combining a multiple-comparison test for dose-response signal with model fitting for dose selection. Version 1.3.0 added functions and vignettes for the binary endpoint case, opening the package beyond the continuous endpoints it was built around, and 1.3.2 followed with Firth's penalized regression to handle separation in those binary fits. The same 1.3.0 release let assessDesign() accept custom simulated data and custom model estimates, which moves simulation control out of the package and into the user's hands.
What is dataSDA?
dataSDA grew from a dataset collection into a symbolic-data conversion toolkit.
The package now carries 105 documented datasets in interval, histogram, modal, and mixed symbolic formats, drawn from other R packages, the Billard and Diday textbooks, and public sources such as the Portuguese air quality network. Alongside the data it has accumulated conversion functions between the MM, RSDA, iGAP, SODAS, and ARRAY representations, CSV read and write support, and a keyword search over the catalogue.
BayesianMCPMod vs dataSDA: editorial side-by-side
BayesianMCPMod
0.0INFRA · APIS
A Bayesian dose-finding package extends from continuous endpoints to binary ones
◆ Current state
BayesianMCPMod implements the Bayesian form of MCP-Mod for dose-finding trials, combining a multiple-comparison test for dose-response signal with model fitting for dose selection. Version 1.3.0 added functions and vignettes for the binary endpoint case, opening the package beyond the continuous endpoints it was built around, and 1.3.2 followed with Firth's penalized regression to handle separation in those binary fits. The same 1.3.0 release let assessDesign() accept custom simulated data and custom model estimates, which moves simulation control out of the package and into the user's hands.
◆ Where it's heading
Each release has widened the estimands and data shapes the framework accepts rather than changing its statistical core. 1.0.2 added non-monotonic beta and quadratic model shapes; 1.1.0 introduced getMED() for the minimally efficacious dose and parallel execution through the future framework; 1.2.0 switched the posterior and contrast functions from a standard deviation vector to a full covariance matrix and supported non-zero off-diagonals in the MCP step. The binary endpoint work is the same pattern applied to the outcome type, and the Firth addition shows the follow-through of a maintainer who has hit the separation problem in practice.
◆ Prediction
Expect the binary endpoint arm to keep filling in - more diagnostics and design assessment coverage matching what the continuous case already has - since 1.3.2 addressed a specific estimation failure rather than adding a new capability.
dataSDA
2.5INFRA · APIS
dataSDA grew from a dataset collection into a symbolic-data conversion toolkit.
◆ Current state
The package now carries 105 documented datasets in interval, histogram, modal, and mixed symbolic formats, drawn from other R packages, the Billard and Diday textbooks, and public sources such as the Portuguese air quality network. Alongside the data it has accumulated conversion functions between the MM, RSDA, iGAP, SODAS, and ARRAY representations, CSV read and write support, and a keyword search over the catalogue.
◆ Where it's heading
The arc across this window runs from cataloguing to tooling. Early releases added datasets and then spent two consecutive releases fixing format documentation across all 105 of them. Later releases shift to functions: format converters, symbolic CSV I/O, and most recently a diagnostic that flags zero-width intervals before they reach tools that divide by interval width. That last addition is the clearest signal of intent — the package is starting to guard the analyses downstream of it, not just supply inputs.
◆ Prediction
Expect further validation helpers in the mould of the zero-width check, since interval data has several degenerate shapes that break downstream methods silently.
Alternatives to BayesianMCPMod and dataSDA
Other Infra & APIs 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 BayesianMCPMod or dataSDA.
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estimatr
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ggdist
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ipaddress
IP address vectors for R that hit 1.0 and then went quiet.
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See all BayesianMCPMod alternatives → · See all dataSDA alternatives →
Recent activity from BayesianMCPMod and dataSDA
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 9d agodataSDACorrects dataset references and citations
- 2mo agodataSDAAdds zero-width interval diagnostics for symbolic data
- 3mo agoBayesianMCPModFirth penalized regression handles separation in binary endpoints
- 5mo agodataSDAAdds symbolic format converters, CSV I/O, and 11 interval series
- 5mo agoBayesianMCPModRegression fix for missing future.apply, plus credible band options
- 5mo agoBayesianMCPModBinary endpoint support opens the framework past continuous outcomes ⚡
- 5mo agodataSDAFixes column metadata for 19 interval datasets
- 5mo agodataSDACompletes format documentation across all 105 datasets
- 5mo agodataSDAAdds 17 datasets from R packages and reference texts
- 11mo agoBayesianMCPModCovariance matrices replace standard deviation vectors in the MCP step
- 1y agoBayesianMCPModMinimally efficacious dose estimation and parallel execution
- 1y agoBayesianMCPModNon-monotonic beta and quadratic dose-response shapes
Frequently asked questions
What is the difference between BayesianMCPMod and dataSDA?
Both compete on the same themes — r-package — within Infra & APIs. dataSDA is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is BayesianMCPMod better than dataSDA?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dataSDA is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
What are the best alternatives to BayesianMCPMod?
Top BayesianMCPMod alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "BayesianMCPMod alternatives" section above for the current picks, or visit /alternatives/bayesianmcpmod for the full list with editorial commentary on each.
What are the best alternatives to dataSDA?
Top dataSDA alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "dataSDA alternatives" section above for the current picks, or visit /alternatives/datasda for the full list with editorial commentary on each.