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ggeffects vs loo

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

Shared themes:r-stats

ggeffects vs loo: at a glance

Featureggeffectsloo
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesmarginal-effects, r-stats, statistics, breaking-changesbayesian, cross-validation, stan, r-stats
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is ggeffects?

ggeffects hands its contrast engine to modelbased and keeps the interface

ggeffects computes and plots marginal effects for a long tail of R model classes. Its recent line has two threads: steadily broadening model support and argument surface, and repeatedly absorbing breaking changes from the packages it computes on top of. In 2.2.0 it stopped absorbing them and delegated test_predictions() and johnson_neyman() to modelbased instead.

Read the full ggeffects trajectory →

What is loo?

loo keeps rewriting the diagnostics Bayesian modellers read off model comparison

loo computes leave-one-out cross-validation and model comparison for Bayesian models in the Stan ecosystem. Two releases in this window changed what users actually read: 2.7.0 replaced the fixed Pareto-k thresholds with sample-size-dependent ones and dropped the middle category, and 2.10.0 reshaped loo_compare's output into a data.frame with new uncertainty columns. The releases between are diagnostic robustness fixes and moment-matching corrections.

Read the full loo trajectory →

ggeffects vs loo: editorial side-by-side

G
ggeffects
ANALYTICS
0.0

ggeffects hands its contrast engine to modelbased and keeps the interface

◆ Current state

ggeffects computes and plots marginal effects for a long tail of R model classes. Its recent line has two threads: steadily broadening model support and argument surface, and repeatedly absorbing breaking changes from the packages it computes on top of. In 2.2.0 it stopped absorbing them and delegated test_predictions() and johnson_neyman() to modelbased instead.

◆ Where it's heading

The package is settling into a front-end role — a consistent predict_response() interface over other people's estimation engines — rather than owning the computation itself. The 2.x releases also show a pattern of removing deprecated arguments and clarifying mixed-model semantics, so the interface is being tightened as the backend is outsourced.

◆ Prediction

Expect the features lost in the modelbased handover to return as that package's contrast and slope estimation matures, rather than being reimplemented locally.

L
loo
ANALYTICS
2.5

loo keeps rewriting the diagnostics Bayesian modellers read off model comparison

◆ Current state

loo computes leave-one-out cross-validation and model comparison for Bayesian models in the Stan ecosystem. Two releases in this window changed what users actually read: 2.7.0 replaced the fixed Pareto-k thresholds with sample-size-dependent ones and dropped the middle category, and 2.10.0 reshaped loo_compare's output into a data.frame with new uncertainty columns. The releases between are diagnostic robustness fixes and moment-matching corrections.

◆ Where it's heading

The package is being brought in line with the current PSIS literature rather than extended with new features, and the practical effect is that the numbers practitioners quote in papers keep changing meaning. Work is increasingly delegated to posterior for shared computations, and the project has added contributor process, benchmarks and a published AI contribution policy.

◆ Prediction

Expect further work on comparison diagnostics — the p_worse and diag_* columns are new enough that their defaults and documentation will likely be revised next.

Alternatives to ggeffects and loo

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 ggeffects or loo.

See all ggeffects alternatives → · See all loo alternatives →

Recent activity from ggeffects and loo

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

  1. 20d agoloopsis_smooth_tail revert and simplify arg restored
  2. 1mo agolooloo_compare returns a data.frame with new uncertainty columns
  3. 7mo agolooStacking overflow fixes and posterior-based ESS
  4. 1y agoggeffectsggeffects delegates contrasts and slopes to modelbased
  5. 1y agoggeffectsFive focal terms and formula-based contrast tests
  6. 1y agoggeffectsMixed-model predictions split type from interval
  7. 1y agoggeffectsBias correction for back-transformed mixed-model predictions
  8. 1y agoggeffectsSupport for WeightIt model classes
  9. 2y agolooMore robust Pareto-k diagnostics and moment matching
  10. 2y agoggeffectsglmgee support and vcov controls for ggemmeans()
  11. 2y agolooPareto-k thresholds now depend on sample size
  12. 3y agolooLOO predictive metrics and CRPS scoring functions

Frequently asked questions

What is the difference between ggeffects and loo?

Both compete on the same themes — r-stats — within Analytics. loo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is ggeffects better than loo?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. loo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to ggeffects?

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

What are the best alternatives to loo?

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