STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of rempsyc and slope — release velocity, themes, recent moves, and the top alternatives to consider.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.
A year after gutting itself for a C++ rewrite, SLOPE is back to polishing the interface
SLOPE fits sorted L-one penalized regression models. In July 2025 it replaced its entire solver with the external libslope C++ library, removing the ADMM solver, dropping debugging fields, changing alpha scaling and warning users directly that the breakage was extensive. The releases since have rebuilt convenience on top of that core: summary() and refit() methods for cross-validated objects, automatic refitting in cvSLOPE(), and a threading default reduced from half the available cores to one.
rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.
Two forces drive this package and neither is its own roadmap. The first is APA style: when the 7th edition advised against beta for standardized coefficients, the package switched its output to italic b with an asterisk. The second is the surrounding ecosystem — formatting is aligned to what lavaanExtra and afex produce, contrast handling was delegated to easystats' modelbased, and Excel correlation matrix export was handed entirely to the correlation package to cut maintenance.
The pattern of delegating functionality to specialist packages while keeping the formatting layer is well established and likely continues. Because releases bundle many small dev versions, the next one will probably again mix plotting refinements with fixes surfaced by upstream changes.
SLOPE fits sorted L-one penalized regression models. In July 2025 it replaced its entire solver with the external libslope C++ library, removing the ADMM solver, dropping debugging fields, changing alpha scaling and warning users directly that the breakage was extensive. The releases since have rebuilt convenience on top of that core: summary() and refit() methods for cross-validated objects, automatic refitting in cvSLOPE(), and a threading default reduced from half the available cores to one.
The arc runs rewrite, then repair, then convenience. The 1.2.0 release is the repair phase — coefficients_scaled was returning unscaled values, which silently affected every coef.SLOPE() call — and 2.0.0 onward is convenience, with refit() now working without re-supplying training data. The tag timestamps are non-monotonic: 1.0.1 is stamped a minute after 1.1.0 despite the lower version, so ordering here reflects when tags were pushed, not what superseded what.
With the cross-validation workflow now closing itself out through automatic refitting, further work is more likely to extend the summary and plotting surface than to touch the solver again.
Other Analytics 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 rempsyc or slope.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all rempsyc alternatives → · See all slope alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. rempsyc and slope 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. rempsyc and slope 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 Analytics products to evaluate alongside.
Top rempsyc alternatives in Analytics are ranked by recent ship velocity. Browse the "rempsyc alternatives" section above for the current picks, or visit /alternatives/rempsyc for the full list with editorial commentary on each.
Top slope alternatives in Analytics are ranked by recent ship velocity. Browse the "slope alternatives" section above for the current picks, or visit /alternatives/slope for the full list with editorial commentary on each.