pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of metagroup and mice — release velocity, themes, recent moves, and the top alternatives to consider.
A first release that turns meta-analytic heterogeneity into interpretable subgroups.
metagroup reached CRAN in late August with a complete first release: eight grouping functions covering binary, continuous, correlational, proportion, incidence and generic inverse-variance data, plus interpretation and plotting on top. The two releases since are CRAN review housekeeping. The package has shipped nothing but its launch.
mice can finally predict, not just estimate, from multiply imputed data.
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
metagroup reached CRAN in late August with a complete first release: eight grouping functions covering binary, continuous, correlational, proportion, incidence and generic inverse-variance data, plus interpretation and plotting on top. The two releases since are CRAN review housekeeping. The package has shipped nothing but its launch.
The design is a two-step pipeline, partitioning studies into homogeneous clusters and then characterising what those clusters have in common, which puts interpretation rather than detection at the centre. The follow-up releases suggest the author is still clearing the CRAN intake process rather than extending the method.
The next substantive release most likely broadens the interpretation side, since the grouping functions already cover the standard effect-size types.
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
Two things are happening. The imputation method catalogue keeps widening — lasso variants, multivariate PMM, categorical PMM via canonical correlation — while the pooling side is being extended past its original purpose, first to synthetic data, now to predictions on held-out sets. That second thread points at predictive modelling workflows rather than the inferential ones mice was built for. Meanwhile the maintainers keep finding consequential old bugs: the augment() ordered-factor defect in 3.18.0 had been silently degrading ordinal imputations for years.
predict_mi() is framed around evaluating predictive performance on test sets, and the ignore argument added in 3.12.0 already exists to hold out rows from the imputation model. Expect the next work to join those up into a fuller train/test story for imputed data, since the pieces are now in place but not yet connected.
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 metagroup or mice.
The protist reference database keeps widening past the rRNA gene it was built on.
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
Conservation planning absorbs the literature's target-setting rules as code.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
An ecosystem model starts tracking carbon isotopes and land-use change.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
See all metagroup alternatives → · See all mice alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. metagroup and mice 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. metagroup and mice 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 metagroup alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "metagroup alternatives" section above for the current picks, or visit /alternatives/metagroup for the full list with editorial commentary on each.
Top mice alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mice alternatives" section above for the current picks, or visit /alternatives/mice for the full list with editorial commentary on each.