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betaselectr vs DHARMa

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

Shared themes:r-package

betaselectr vs DHARMa: at a glance

FeaturebetaselectrDHARMa
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesstandardised-coefficients, regression, psychometrics, cranresidual-diagnostics, glmm, breaking-change, bayesian
Last editorial update22m ago1h ago
WebsiteVisit →Visit →

What is betaselectr?

Standardised coefficients for models where standardising everything is wrong — but the feed only links out

betaselectr computes standardised coefficients selectively, for models where blanket standardisation misleads — interaction terms, categorical predictors and moderated effects, where standardising the product term or a dummy variable produces a number that does not mean what readers assume. It has been on CRAN since November 2024 across three releases. What those releases contain cannot be determined from this feed.

Read the full betaselectr trajectory →

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.

Read the full DHARMa trajectory →

betaselectr vs DHARMa: editorial side-by-side

B
betaselectr
ANALYTICS
0.0

Standardised coefficients for models where standardising everything is wrong — but the feed only links out

◆ Current state

betaselectr computes standardised coefficients selectively, for models where blanket standardisation misleads — interaction terms, categorical predictors and moderated effects, where standardising the product term or a dummy variable produces a number that does not mean what readers assume. It has been on CRAN since November 2024 across three releases. What those releases contain cannot be determined from this feed.

◆ Where it's heading

This changelog carries no release content. Every entry is a pointer to the CRAN page and to a changelog hosted on the package's own site, so the direction of development is not readable from what is published here. What the version numbers alone support is a package that reached CRAN in late 2024 and has issued two patch releases since, at roughly six-month intervals, without a minor version bump.

◆ Prediction

No prediction is supportable from these entries; the feed would need to carry actual release notes, or the package's own site would need to be read directly, before its direction could be called.

D
DHARMa
ANALYTICS
0.0

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 betaselectr 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 betaselectr or DHARMa.

See all betaselectr alternatives → · See all DHARMa alternatives →

Recent activity from betaselectr and DHARMa

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

  1. 2mo agoDHARMaConditional simulation becomes the GLMM default, changing residuals
  2. 9mo agobetaselectrCRAN Release 0.1.3
  3. 1y agobetaselectrCRAN Release 0.1.2
  4. 1y agobetaselectrCRAN Release 0.1.0
  5. 1y agoDHARMaDHARMa 0.4.7
  6. 3y agoDHARMaDHARMa 0.4.6
  7. 4y agoDHARMaDHARMa 0.4.5
  8. 4y agoDHARMaDHARMa 0.4.4
  9. 5y agoDHARMaDHARMa 0.4.3

Frequently asked questions

What is the difference between betaselectr and DHARMa?

Both compete on the same themes — r-package — within Analytics. betaselectr 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 betaselectr better than DHARMa?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. betaselectr 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 betaselectr?

Top betaselectr alternatives in Analytics are ranked by recent ship velocity. Browse the "betaselectr alternatives" section above for the current picks, or visit /alternatives/betaselectr 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.