← Back to home
Comparison · Analytics

epikit vs fairmodels

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

epikit vs fairmodels: at a glance

Featureepikitfairmodels
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesepidemiology, field-data, date-handling, r-packagefairness auditing, bias detection, dalex, r package
Last editorial update52m ago7h ago
WebsiteVisit →Visit →

What is epikit?

epikit narrows to field-epidemiology helpers, handing proportions to a sibling package

epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.

Read the full epikit trajectory →

What is fairmodels?

fairmodels sits dormant for three years, resurfacing only to satisfy a CRAN check.

fairmodels audits classification models for bias, built around fairness_check() and parity-loss metrics on top of DALEX explainers. The last substantive work dates from 2021; the 2025 release is a single-line change swapping ifelse for if/else in fairness_heatmap. Version 0.2.2 set the package's core design when it superseded metric differences with ratios.

Read the full fairmodels trajectory →

epikit vs fairmodels: editorial side-by-side

E
epikit
ANALYTICS
0.0

epikit narrows to field-epidemiology helpers, handing proportions to a sibling package

◆ Current state

epikit is a set of small helpers for applied epidemiology in R — age categorisation, date reconstruction from partial records, and related field-data chores, developed in the R4Epis orbit. Version 0.2.0 moved the proportion functions out to epitabulate, improved how find_date_cause(), find_start_date() and find_end_date() handle dates falling outside the period, and added a floor argument to age_categories() so the lowest band reads as under one rather than zero to zero.

◆ Where it's heading

The package is being scoped down rather than built out. The 0.1.3 restructuring and the 0.2.0 handover of proportions to epitabulate are the same move made twice: push functionality into the package where it belongs and keep epikit to the toolkit that field epidemiologists reach for directly. The rest of the history is dependency compatibility work against dplyr and tibble.

◆ Prediction

With proportions gone and dependencies trimmed, the remaining functions cluster tightly around dates and age bands, so further refinement of the date-reconstruction helpers is more likely than new capability areas.

F
fairmodels
ANALYTICS
0.0

fairmodels sits dormant for three years, resurfacing only to satisfy a CRAN check.

◆ Current state

fairmodels audits classification models for bias, built around fairness_check() and parity-loss metrics on top of DALEX explainers. The last substantive work dates from 2021; the 2025 release is a single-line change swapping ifelse for if/else in fairness_heatmap. Version 0.2.2 set the package's core design when it superseded metric differences with ratios.

◆ Where it's heading

The release history describes a package that reached its intended shape early and has been custodial since — the gap from August 2022 to October 2025 carries no functional change at all. What movement exists is CRAN-driven: documentation compliance, example runtimes, coding-style notes. The fairness metrics themselves have not changed since the parity_loss corrections of 2020.

◆ Prediction

On this cadence the next release is most likely another CRAN-prompted one-liner rather than new fairness metrics; nothing in these entries points to active development.

Alternatives to epikit and fairmodels

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 epikit or fairmodels.

See all epikit alternatives → · See all fairmodels alternatives →

Recent activity from epikit and fairmodels

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

  1. 9mo agoepikitProportion functions moved to epitabulate; date helpers warn correctly
  2. 9mo agofairmodelsOne-line fix in fairness_heatmap
  3. 3y agofairmodelsCRAN compliance fixes and citation update
  4. 3y agoepikitFunctions rearranged across sibling packages
  5. 4y agofairmodelsCRAN v1.2.0
  6. 5y agofairmodelsCRAN v1.1.0
  7. 5y agofairmodelsDocumentation fixes and trimmed example runtimes
  8. 5y agofairmodelsCorrects parity_loss in the cutoff functions
  9. 5y agoepikitRaise dplyr and tibble minimums; move CI to GitHub Actions
  10. 5y agoepikitCompatibility release for dplyr 1.0.0
  11. 6y agoepikitFirst CRAN release

Frequently asked questions

What is the difference between epikit and fairmodels?

They serve adjacent needs but don't currently overlap on shipped themes. epikit and fairmodels 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 epikit better than fairmodels?

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

What are the best alternatives to epikit?

Top epikit alternatives in Analytics are ranked by recent ship velocity. Browse the "epikit alternatives" section above for the current picks, or visit /alternatives/epikit-r for the full list with editorial commentary on each.

What are the best alternatives to fairmodels?

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