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Comparison · Infra & APIs

ggprism vs mice

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

ggprism vs mice: at a glance

Featureggprismmice
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, themes, visualization, compatibilitymissing-data, multiple-imputation, statistics, r-package
Last editorial update43m ago1h ago
WebsiteVisit →Visit →

What is ggprism?

A Prism-styled ggplot2 theme in maintenance, now surviving ggplot2 4.0.

ggprism reproduces GraphPad Prism's look inside ggplot2 through themes, axis guides, palettes and p-value brackets, and has been feature-stable since its 2021 CRAN debut. The only release in the recent window is a compatibility pass for ggplot2 v4.0.0. The rest of the visible history is the original 2021 launch sequence.

Read the full ggprism trajectory →

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 →

ggprism vs mice: editorial side-by-side

G
ggprism
INFRA · APIS
0.0

A Prism-styled ggplot2 theme in maintenance, now surviving ggplot2 4.0.

◆ Current state

ggprism reproduces GraphPad Prism's look inside ggplot2 through themes, axis guides, palettes and p-value brackets, and has been feature-stable since its 2021 CRAN debut. The only release in the recent window is a compatibility pass for ggplot2 v4.0.0. The rest of the visible history is the original 2021 launch sequence.

◆ Where it's heading

The package now moves on upstream's clock rather than its own: releases appear when ggplot2 makes a breaking change, and the content is deprecation cleanup and test repair. The 2021 entries show where the capability surface was set, and it has not widened since.

◆ Prediction

The next release is most likely another ggplot2 compatibility pass rather than new guides or palettes.

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.

Alternatives to ggprism and mice

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 ggprism or mice.

See all ggprism alternatives → · See all mice alternatives →

Recent activity from ggprism and mice

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

  1. 8mo agomicemice 3.19.0
  2. 1y agoggprismggplot2 4.0 compatibility fixes for theme_prism()
  3. 1y agomicemice 3.18.0
  4. 1y agomicemice 3.17.0
  5. 3y agomicemice 3.16.0
  6. 3y agomicemice 3.15.0
  7. 4y agomicemice 3.14.0
  8. 5y agoggprismVignette figure and test fixes ahead of ggplot2 3.4
  9. 5y agoggprismadd_pvalue() accepts more input column layouts
  10. 5y agoggprismFirst CRAN submission after the GitHub release
  11. 5y agoggprismInitial release: Prism themes, guides, palettes, p-value brackets

Frequently asked questions

What is the difference between ggprism and mice?

They serve adjacent needs but don't currently overlap on shipped themes. ggprism 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.

Is ggprism better than mice?

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

What are the best alternatives to ggprism?

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

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.