mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of midr and serocalculator — release velocity, themes, recent moves, and the top alternatives to consider.
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
midr explains black-box models by fitting an interpretable surrogate through Maximum Interpretation Decomposition — main effects plus second-order interactions, with exact Shapley values for the surrogate. Two months after its first CRAN release it can take a matrix response, which covers multi-class classification and survival models, and hold collections of fitted interpretations in midlist and midrib objects for comparison.
A seroincidence engine grows up: whole API renamed, then clustered survey designs
serocalculator turns cross-sectional antibody measurements into infection-rate estimates, and it spent its last two releases making itself safe to depend on. Version 1.4.0 renamed nearly every user-facing function into a consistent est_seroincidence()/sr_params vocabulary; 1.4.1 shipped the migration crosswalk that admits how much that broke. The newest capability is cluster-robust variance estimation for household- and school-based surveys.
midr explains black-box models by fitting an interpretable surrogate through Maximum Interpretation Decomposition — main effects plus second-order interactions, with exact Shapley values for the surrogate. Two months after its first CRAN release it can take a matrix response, which covers multi-class classification and survival models, and hold collections of fitted interpretations in midlist and midrib objects for comparison.
The releases move outward along two axes at once: what can be interpreted, and how much of it fits in memory. Version 0.5.3 rebuilt the fitting path to avoid materialising large design matrices and added a save.memory option; 0.6.0 widened the response from a vector to a matrix and added parametric link functions. Class and argument names were shortened in the same release, so the package is still willing to break itself this early.
With multiple models now held in one object and visualisation methods for them, comparison across models is the surface most likely to fill out next — the collection classes exist but the notes describe manipulation and plotting rather than any comparison metric.
serocalculator turns cross-sectional antibody measurements into infection-rate estimates, and it spent its last two releases making itself safe to depend on. Version 1.4.0 renamed nearly every user-facing function into a consistent est_seroincidence()/sr_params vocabulary; 1.4.1 shipped the migration crosswalk that admits how much that broke. The newest capability is cluster-robust variance estimation for household- and school-based surveys.
The arc runs from method to instrument. Early releases added example data and plotting; recent ones fix the API surface, satisfy CRAN's offline-failure policy, and extend the estimator to sampling designs field epidemiology actually uses — multi-level clustering, stratification, and the two combined. Each release also carries visible refactoring discipline (one function per file, linting, per-PR website previews) that reads like a package preparing for contributors it does not have yet.
With cluster_var and stratum_var now threaded through both est_seroincidence() and est_seroincidence_by(), survey weights are the remaining piece of a complex-survey design the sandwich estimator does not cover. The entries do not name it, so read that as direction rather than a promise.
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 midr or serocalculator.
mice can finally predict, not just estimate, from multiply imputed data.
A market-microstructure toolkit that keeps adding estimators as the papers land.
A vowel-analysis package trimming dependencies after an email address got it archived.
The R half of the EMU speech database system, fixing what was quietly broken.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
tidyplots keeps rebuilding its own foundations rather than layering around them.
See all midr alternatives → · See all serocalculator alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. midr and serocalculator 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. midr and serocalculator 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 Infra & APIs products to evaluate alongside.
Top midr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "midr alternatives" section above for the current picks, or visit /alternatives/midr for the full list with editorial commentary on each.
Top serocalculator alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "serocalculator alternatives" section above for the current picks, or visit /alternatives/serocalculator for the full list with editorial commentary on each.