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Comparison · Infra & APIs

mice vs tidyplots

A side-by-side editorial comparison of mice and tidyplots — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:statisticsr-package

mice vs tidyplots: at a glance

Featuremicetidyplots
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesmissing-data, multiple-imputation, statistics, r-packagedata-visualization, r-package, ggplot2, scientific-publishing
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is mice?

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.

Read the full mice trajectory →

What is tidyplots?

tidyplots keeps rebuilding its own foundations rather than layering around them.

tidyplots wraps ggplot2 in a pipe-driven API aimed at publication-ready scientific figures, trading grammar-of-graphics flexibility for a shorter path to a finished plot. It is at 0.4.0 after two years of frequent releases, and almost every one carries a breaking change — the most recent moved multi-panel layout off patchwork and onto ggplot2's own faceting. Statistical annotation, colour schemes and size control have each been reworked at least once.

Read the full tidyplots trajectory →

mice vs tidyplots: editorial side-by-side

M
mice
INFRA · APIS
0.0

mice can finally predict, not just estimate, from multiply imputed data.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

T
tidyplots
INFRA · APIS
0.0

tidyplots keeps rebuilding its own foundations rather than layering around them.

◆ Current state

tidyplots wraps ggplot2 in a pipe-driven API aimed at publication-ready scientific figures, trading grammar-of-graphics flexibility for a shorter path to a finished plot. It is at 0.4.0 after two years of frequent releases, and almost every one carries a breaking change — the most recent moved multi-panel layout off patchwork and onto ggplot2's own faceting. Statistical annotation, colour schemes and size control have each been reworked at least once.

◆ Where it's heading

The package is converging on ggplot2 rather than abstracting away from it: split_plot() now uses facet_wrap and facet_grid, as_tidyplot() was hard-deprecated on the grounds that converting a ggplot was never a good idea, and releases are timed against upstream ggplot2 versions. The other constant is the statistics surface, which has grown from basic error bars to paired and selected comparisons. Breaking changes are announced plainly and frequently, consistent with a package using 0.x to fix its shape before committing.

◆ Prediction

The patchwork removal is described as something that will eventually break dependent code, so the near-term work is likely completing that migration and settling the split_plot() parameters introduced alongside it. A 1.0 would signal the breaking-change cadence is ending, and nothing here indicates that yet.

Alternatives to mice and tidyplots

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 tidyplots.

See all mice alternatives → · See all tidyplots alternatives →

Recent activity from mice and tidyplots

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 7mo agotidyplotstidyplots 0.4.0
  2. 8mo agomicemice 3.19.0
  3. 1y agotidyplotstidyplots 0.3.1
  4. 1y agomicemice 3.18.0
  5. 1y agotidyplotstidyplots 0.2.2
  6. 1y agotidyplotstidyplots 0.2.1
  7. 1y agotidyplotstidyplots 0.2.0
  8. 1y agomicemice 3.17.0
  9. 1y agotidyplotstidyplots 0.1.2
  10. 3y agomicemice 3.16.0
  11. 3y agomicemice 3.15.0
  12. 4y agomicemice 3.14.0

Frequently asked questions

What is the difference between mice and tidyplots?

Both compete on the same themes — statistics, r-package — within Infra & APIs. mice and tidyplots 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.

Is mice better than tidyplots?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mice and tidyplots 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.

What are the best alternatives to mice?

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.

What are the best alternatives to tidyplots?

Top tidyplots alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "tidyplots alternatives" section above for the current picks, or visit /alternatives/tidyplots for the full list with editorial commentary on each.