cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
Comparison · Analytics
dcurves vs DHARMa
A side-by-side editorial comparison of dcurves and DHARMa — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
dcurves vs DHARMa: at a glance
What is dcurves?
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
dcurves implements decision curve analysis — evaluating a prediction model or diagnostic test by net benefit across the range of thresholds a clinician might plausibly use, rather than by a single discrimination statistic. Its API stabilised in 2022 around dca() and test_consequences(). The two releases since exist because gtsummary and CRAN documentation rules changed, not because the method did.
What is DHARMa?
DHARMa changed how GLMM residuals are simulated, so the same code now returns different numbers.
DHARMa generates scaled quantile residuals for fitted GLMMs and runs the dispersion, uniformity, and autocorrelation tests built on them. Version 0.5.0 changed the default simulation for hierarchical models from the model's own default, mostly unconditional, to conditional simulation, and states plainly that residuals will differ from those computed by older versions. The same release added brms to the supported model set and reworked how predictors are passed to plotting and testing functions.
dcurves vs DHARMa: editorial side-by-side
dcurves
0.0ANALYTICS
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
◆ Current state
dcurves implements decision curve analysis — evaluating a prediction model or diagnostic test by net benefit across the range of thresholds a clinician might plausibly use, rather than by a single discrimination statistic. Its API stabilised in 2022 around dca() and test_consequences(). The two releases since exist because gtsummary and CRAN documentation rules changed, not because the method did.
◆ Where it's heading
The package reached its intended scope quickly and then stopped. Its 2022 releases did the substantive work: adding threshold-level diagnostic accuracy, tightening argument validation, and taking one breaking change to make net-interventions-avoided plots show the treat-all and treat-none reference lines by default. Since then it has moved only as a dependent of the wider tidy-modelling documentation ecosystem it plugs into.
◆ Prediction
Nothing in these entries points to method or API work; expect the next release to be another compatibility or CRAN documentation patch.
DHARMa
0.0ANALYTICS
DHARMa changed how GLMM residuals are simulated, so the same code now returns different numbers.
◆ Current state
DHARMa generates scaled quantile residuals for fitted GLMMs and runs the dispersion, uniformity, and autocorrelation tests built on them. Version 0.5.0 changed the default simulation for hierarchical models from the model's own default, mostly unconditional, to conditional simulation, and states plainly that residuals will differ from those computed by older versions. The same release added brms to the supported model set and reworked how predictors are passed to plotting and testing functions.
◆ Where it's heading
The package has spent several releases widening which model backends it can diagnose, from glmmTMB through mgcv, phylolm and now brms, while methodological work has gone into handling correlated residuals via the rotation argument. Version 0.5.0 shifts from adding coverage to changing defaults for statistical power. The formula interface arriving across plotResiduals, testCategorical, testQuantiles and the autocorrelation tests suggests the API is being unified rather than extended function by function.
◆ Prediction
The next releases will likely broaden brms support past the simple-model restriction and continue converting remaining functions to the formula interface.
Alternatives to dcurves and DHARMa
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 dcurves or DHARMa.
MetaboAnalystR
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
fmtr
Rebuilding SAS's formatting layer in R, one format specification at a time
betaselectr
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
SSN2
Stream-network spatial models learning to run on data that no longer fits in memory
BiocManager
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
See all dcurves alternatives → · See all DHARMa alternatives →
Recent activity from dcurves and DHARMa
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agoDHARMaConditional simulation becomes the GLMM default, changing residuals ⚡
- 9mo agodcurvesHTML5 documentation rebuild for CRAN
- 1y agoDHARMaDHARMa 0.4.7
- 2y agodcurvesbroom.helpers added to Suggests for gtsummary 2.0
- 3y agodcurvesNet interventions plots now show treat-all and treat-none by default
- 3y agoDHARMaDHARMa 0.4.6
- 4y agodcurvestest_consequences() reports accuracy across thresholds
- 4y agoDHARMaDHARMa 0.4.5
- 4y agoDHARMaDHARMa 0.4.4
- 5y agoDHARMaDHARMa 0.4.3
Frequently asked questions
What is the difference between dcurves and DHARMa?
Both compete on the same themes — r-package — within Analytics. dcurves and DHARMa 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 dcurves better than DHARMa?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dcurves and DHARMa 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 dcurves?
Top dcurves alternatives in Analytics are ranked by recent ship velocity. Browse the "dcurves alternatives" section above for the current picks, or visit /alternatives/dcurves for the full list with editorial commentary on each.
What are the best alternatives to DHARMa?
Top DHARMa alternatives in Analytics are ranked by recent ship velocity. Browse the "DHARMa alternatives" section above for the current picks, or visit /alternatives/dharma for the full list with editorial commentary on each.