cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
Comparison · Analytics
dcurves vs ggguides
A side-by-side editorial comparison of dcurves and ggguides — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
dcurves vs ggguides: 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 ggguides?
Three releases in one day to make legend positioning finally do what the docs said.
ggguides is a helper layer over ggplot2's guide system, exposing legend placement and styling through small named functions instead of raw theme() calls. On 23 April 2026 it shipped 1.1.7, 1.1.8 and 1.1.9 within thirteen hours, each fixing a different path by which the justification argument silently did nothing. The common root cause is that ggplot2 3.5 split legend.justification into side-specific theme elements, and ggguides was still writing to the generic fallback.
dcurves vs ggguides: 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.
ggguides
0.0ANALYTICS
Three releases in one day to make legend positioning finally do what the docs said.
◆ Current state
ggguides is a helper layer over ggplot2's guide system, exposing legend placement and styling through small named functions instead of raw theme() calls. On 23 April 2026 it shipped 1.1.7, 1.1.8 and 1.1.9 within thirteen hours, each fixing a different path by which the justification argument silently did nothing. The common root cause is that ggplot2 3.5 split legend.justification into side-specific theme elements, and ggguides was still writing to the generic fallback.
◆ Where it's heading
The package is in the phase where a wrapper meets the reality of the API it wraps. All three same-day releases are the same bug found in successive entry points: legend_inside(), then the four side functions, then legend_style(by = ). Along the way the fix work produced a real feature, a justification argument on the side legend functions. The pattern of a single reporter driving three consecutive releases suggests the surface is being audited rather than randomly patched.
◆ Prediction
Expect a consolidation release that audits the remaining theme elements ggguides writes to against ggplot2 3.5 semantics, rather than another single-path fix.
Alternatives to dcurves and ggguides
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 ggguides.
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 ggguides alternatives →
Recent activity from dcurves and ggguides
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agoggguideslegend_style(by=) justification now reaches the whole-plot theme
- 3mo agoggguidesSide legend functions gain justification and target the right theme element
- 3mo agoggguideslegend_inside() justification now moves the legend as documented
- 8mo agoggguidesLegend reordering, key overrides and colorbar styling added
- 9mo agodcurvesHTML5 documentation rebuild for CRAN
- 2y agodcurvesbroom.helpers added to Suggests for gtsummary 2.0
- 3y agodcurvesNet interventions plots now show treat-all and treat-none by default
- 4y agodcurvestest_consequences() reports accuracy across thresholds
Frequently asked questions
What is the difference between dcurves and ggguides?
Both compete on the same themes — r-package — within Analytics. dcurves and ggguides 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 ggguides?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dcurves and ggguides 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 ggguides?
Top ggguides alternatives in Analytics are ranked by recent ship velocity. Browse the "ggguides alternatives" section above for the current picks, or visit /alternatives/ggguides for the full list with editorial commentary on each.