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Comparison · Analytics
ggeffects vs mlr3measures
A side-by-side editorial comparison of ggeffects and mlr3measures — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-stats
ggeffects vs mlr3measures: at a glance
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.
What is mlr3measures?
mlr3measures is systematically retrofitting sample weights across every metric
mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.
ggeffects vs mlr3measures: editorial side-by-side
ggeffects
0.0ANALYTICS
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.
mlr3measures
0.0ANALYTICS
mlr3measures is systematically retrofitting sample weights across every metric
◆ Current state
mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.
◆ Where it's heading
The library is maturing rather than growing: weighted evaluation and observation-wise loss functions are being brought to metrics that already existed, which is what downstream weighted-resampling and per-observation analysis need. The deprecations suggest the maintainers are willing to remove measures they consider ill-defined rather than keep them for compatibility.
◆ Prediction
Expect sample_weights and observation-wise variants to reach the remaining measures that lack them.
Alternatives to ggeffects and mlr3measures
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 mlr3measures.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all ggeffects alternatives → · See all mlr3measures alternatives →
Recent activity from ggeffects and mlr3measures
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agomlr3measuresWeighted AUC and weighted confusion-matrix measures
- 8mo agomlr3measuresObservation-wise loss for bbrier and logloss
- 11mo agomlr3measuresrse, rsq, rrse and rae deprecated; bias measures corrected
- 1y agoggeffectsggeffects delegates contrasts and slopes to modelbased ⚡
- 1y agoggeffectsFive focal terms and formula-based contrast tests
- 1y agoggeffectsMixed-model predictions split type from interval
- 1y agoggeffectsBias correction for back-transformed mixed-model predictions
- 1y agomlr3measureslinex, pinball and Mu AUC measures added
- 1y agoggeffectsSupport for WeightIt model classes
- 2y agomlr3measuresgmean, gpr and multiclass MCC added
- 2y agoggeffectsglmgee support and vcov controls for ggemmeans()
- 4y agomlr3measuresObservation-wise loss functions introduced
Frequently asked questions
What is the difference between ggeffects and mlr3measures?
Both compete on the same themes — r-stats — within Analytics. ggeffects and mlr3measures 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 ggeffects better than mlr3measures?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggeffects and mlr3measures 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 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 mlr3measures?
Top mlr3measures alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3measures alternatives" section above for the current picks, or visit /alternatives/mlr3measures for the full list with editorial commentary on each.