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Comparison · Infra & APIs
cofad vs ddml
A side-by-side editorial comparison of cofad and ddml — release velocity, themes, recent moves, and the top alternatives to consider.
cofad vs ddml: at a glance
What is cofad?
Contrast analysis with a Shiny front end, shipping about one release a year
cofad performs contrast analyses for factorial designs in both between- and within-subject forms, and ships a Shiny GUI alongside the R interface. The 0.3.0 release in 2024 was the substantial one: a helper for calculating differences between two sets of lambdas for competing contrast analysis, improved summary output, removal of the plyr dependency, a rebuilt Shiny interface using standard elements after the sortable drag-and-drop proved unstable, and a change of maintainer to Johannes Titz. The most recent release is a one-line patch fixing degrees of freedom in the t-test table.
What is ddml?
Double machine learning in R keeps adding estimands and the inference to go with them.
ddml implements double and debiased machine learning estimators, with a stacking layer so the nuisance functions can be fit by an ensemble rather than a single learner. The estimand list has grown from partially linear models to average treatment effects, treatment effects on the treated, and local average treatment effects, and 0.3.0 added one-way clustered inference. The most recent release is maintenance: xgboost syntax, glmnet binomial predictions, weights in the flexible partially linear IV estimator.
cofad vs ddml: editorial side-by-side
cofad
0.0INFRA · APIS
Contrast analysis with a Shiny front end, shipping about one release a year
◆ Current state
cofad performs contrast analyses for factorial designs in both between- and within-subject forms, and ships a Shiny GUI alongside the R interface. The 0.3.0 release in 2024 was the substantial one: a helper for calculating differences between two sets of lambdas for competing contrast analysis, improved summary output, removal of the plyr dependency, a rebuilt Shiny interface using standard elements after the sortable drag-and-drop proved unstable, and a change of maintainer to Johannes Titz. The most recent release is a one-line patch fixing degrees of freedom in the t-test table.
◆ Where it's heading
Development is slow and correctness-led. The record runs from a JOSS publication in 2021 through a near three-year gap to a release that both extended the method and repaired the GUI, then a degrees-of-freedom fix. Maintainer and author order changed in 0.3.0, which typically marks a handover rather than a burst of new work, and the cadence since is consistent with that.
◆ Prediction
Expect low-frequency correctness releases; the competing contrast analysis helper added in 0.3.0 is the most likely thing to be extended if anything is.
ddml
0.0INFRA · APIS
Double machine learning in R keeps adding estimands and the inference to go with them.
◆ Current state
ddml implements double and debiased machine learning estimators, with a stacking layer so the nuisance functions can be fit by an ensemble rather than a single learner. The estimand list has grown from partially linear models to average treatment effects, treatment effects on the treated, and local average treatment effects, and 0.3.0 added one-way clustered inference. The most recent release is maintenance: xgboost syntax, glmnet binomial predictions, weights in the flexible partially linear IV estimator.
◆ Where it's heading
Two lines of work run in parallel. One extends what can be estimated, the other makes the estimates trustworthy under real data conditions, and the second is where the recent effort has gone: clustered standard errors, propensity score trimming, higher default fold counts, corrected ATE and LATE scores. Raising sample_folds and cv_folds to ten is a small change with a clear intent, trading compute for stability.
◆ Prediction
Clustered inference arrived one-way; two-way and multi-way clustering are the obvious continuation. The stacking layer is also accumulating edge-case handling, so expect more work on degenerate ensemble weights.
Alternatives to cofad and ddml
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 cofad or ddml.
Warp
Warp turned its quarter of software-factory essays into infrastructure you can buy.
Okta
Okta's developer blog is a Cross App Access campaign, now diluted by advocacy-team storytelling.
tealeaves
A leaf-temperature model that finished its job in 2020 and has stayed finished
Infisical
A credential platform assembled two or three pull requests at a time, never a headline
SigNoz
Search without knowing the field — SigNoz keeps lowering the cost of not knowing your schema
Recent activity from cofad and ddml
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agoddmlFixes for weighted FPLIV, binomial glmnet and empty stacking weights
- 1y agocofadDegrees of freedom corrected in the t-test table
- 1y agoddmlOne-way clustered inference and higher default fold counts
- 2y agocofadCompeting contrast helper, rebuilt Shiny GUI, maintainer change
- 2y agoddmlPropensity score trimming added across the treatment effect estimators
- 2y agoddmlFixes permuted residuals returned by crossval
- 2y agoddmlATT and LATE estimators join the supported estimands
- 4y agocofadDocumentation and references for JOSS publication
- 4y agocofadShiny GUI added; aggregated-data function and 0-variance fix
Frequently asked questions
What is the difference between cofad and ddml?
They serve adjacent needs but don't currently overlap on shipped themes. cofad and ddml 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 cofad better than ddml?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cofad and ddml 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 cofad?
Top cofad alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "cofad alternatives" section above for the current picks, or visit /alternatives/cofad for the full list with editorial commentary on each.
What are the best alternatives to ddml?
Top ddml alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ddml alternatives" section above for the current picks, or visit /alternatives/ddml for the full list with editorial commentary on each.