rollupTree
The recursive-computation engine under massProps grows the accessors its consumer needed
A side-by-side editorial comparison of midr and statpsych — 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 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.
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.
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 midr or statpsych.
The recursive-computation engine under massProps grows the accessors its consumer needed
A mass-properties rollup spends a year on documentation and follows its sibling's API
Six months of releases and not one of them touched the scoring models
A cognitive-science sampling package ships once, then goes quiet for eighteen months
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
Spatial thinning grows a result object, and the API breaks to make room for it
See all midr 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. midr 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. midr 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 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 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.