pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of mice and statpsych — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A statistics catalogue for psychology that grows by the release and rarely changes shape.
statpsych supplies confidence intervals, hypothesis tests, power calculations and sample-size planning for the designs psychology researchers actually run, exposed as several hundred small named functions rather than a modelling framework. Version 2.0.0 adds eight functions across logistic model performance, Kendall tau-a intervals and sample sizes, intraclass correlation testing, Geary kurtosis and Mann-Whitney power, and retires three names in favour of generalised replacements. The major version number reflects those removals rather than a change in how the package is used.
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.
statpsych supplies confidence intervals, hypothesis tests, power calculations and sample-size planning for the designs psychology researchers actually run, exposed as several hundred small named functions rather than a modelling framework. Version 2.0.0 adds eight functions across logistic model performance, Kendall tau-a intervals and sample sizes, intraclass correlation testing, Geary kurtosis and Mann-Whitney power, and retires three names in favour of generalised replacements. The major version number reflects those removals rather than a change in how the package is used.
Every release in this window is the same shape: a list of new functions, occasionally a rename. The package grows by filling cells in a grid of estimand, design and inferential goal, and 2.0.0 is notable only for finally deleting the three names its generalised replacements had superseded. That makes it a reference library whose value is coverage and stability, not direction, and the entries give no sign of that changing.
Expect the accretion to continue along the same axes, with sample-size and power counterparts filled in for estimands that currently have interval functions but no planning ones. The 2.0.0 deletions suggest occasional consolidation passes when a generalised function makes older specific ones redundant.
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 mice or statpsych.
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 mice alternatives → · See all statpsych alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. mice and statpsych 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. mice and statpsych 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 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.
Top statpsych alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "statpsych alternatives" section above for the current picks, or visit /alternatives/statpsych for the full list with editorial commentary on each.