← Back to home
Comparison · Infra & APIs

dscore vs mice

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

Shared themes:r-package

dscore vs mice: at a glance

Featuredscoremice
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themeschild-development, psychometrics, global-health, r-packagemissing-data, multiple-imputation, statistics, r-package
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is dscore?

The D-score reference implementation rebuilt its measurement foundation on seven countries.

dscore computes the D-score and DAZ, the GSED developmental measurement used in child-health research, and it is the reference implementation rather than one option among several. The package is at 2.1.0 after a dense 2025: the default key moved from three-country to seven-country validation data, the licence moved from AGPL to Apache 2.0, and the 2.1.0 line added per-country references, full BSID-III coverage and domain-level scoring. Breaking changes are routine here and always come with a documented fallback key or algorithm argument.

Read the full dscore 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 →

dscore vs mice: editorial side-by-side

D
dscore
INFRA · APIS
0.0

The D-score reference implementation rebuilt its measurement foundation on seven countries.

◆ Current state

dscore computes the D-score and DAZ, the GSED developmental measurement used in child-health research, and it is the reference implementation rather than one option among several. The package is at 2.1.0 after a dense 2025: the default key moved from three-country to seven-country validation data, the licence moved from AGPL to Apache 2.0, and the 2.1.0 line added per-country references, full BSID-III coverage and domain-level scoring. Breaking changes are routine here and always come with a documented fallback key or algorithm argument.

◆ Where it's heading

The arc runs from correcting the instrument to broadening who can use it. The 2020-2024 releases were item-table repair and error correction, including a scale-factor bug that altered published standard errors; from 1.11.0 onward the work is distribution — a permissive licence, more instruments mapped in, and references resolved per country rather than pooled. That combination points at national-survey and app-embedded use rather than research-only use.

◆ Prediction

The 2.0.0 notes state that groundwork was laid for extending D-scores to older children, and 2.0.0 still tells users to fall back to gsed2406 for instruments outside GSED SF and LF. Expect the next releases to close that gap by mapping more instruments into gsed2510, with the older-age extension the likeliest headline feature.

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 dscore 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 dscore or mice.

See all dscore alternatives → · See all mice alternatives →

Recent activity from dscore and mice

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

  1. 7mo agodscoredscore 2.1.0
  2. 8mo agomicemice 3.19.0
  3. 10mo agodscoredscore 2.0.0
  4. 10mo agodscoredscore 1.11.0
  5. 1y agodscoredscore 1.10.0
  6. 1y agomicemice 3.18.0
  7. 1y agomicemice 3.17.0
  8. 2y agodscoredscore 1.9.0
  9. 3y agomicemice 3.16.0
  10. 3y agodscoredscore 1.7.0
  11. 3y agomicemice 3.15.0
  12. 4y agomicemice 3.14.0

Frequently asked questions

What is the difference between dscore and mice?

Both compete on the same themes — r-package — within Infra & APIs. dscore 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 dscore better than mice?

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

Top dscore alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "dscore alternatives" section above for the current picks, or visit /alternatives/dscore 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.