cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
Comparison · Analytics
DHARMa vs fmtr
A side-by-side editorial comparison of DHARMa and fmtr — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
DHARMa vs fmtr: at a glance
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.
What is fmtr?
Rebuilding SAS's formatting layer in R, one format specification at a time
fmtr applies formats to R data the way SAS applies them: named format catalogues, format lists, and an fapply() that maps a specification onto a vector. It is part of a family of packages that reconstruct SAS reporting idioms in R, and it shares infrastructure with them — labels.data.frame() was moved out to the common package, which fmtr now depends on. The recent releases have been closing specific gaps against SAS's own format vocabulary.
DHARMa vs fmtr: editorial side-by-side
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.
fmtr
0.0ANALYTICS
Rebuilding SAS's formatting layer in R, one format specification at a time
◆ Current state
fmtr applies formats to R data the way SAS applies them: named format catalogues, format lists, and an fapply() that maps a specification onto a vector. It is part of a family of packages that reconstruct SAS reporting idioms in R, and it shares infrastructure with them — labels.data.frame() was moved out to the common package, which fmtr now depends on. The recent releases have been closing specific gaps against SAS's own format vocabulary.
◆ Where it's heading
The direction is parity, pursued in small increments. Quarter format codes were added because base R has none; the SAS best. format was reimplemented, then hardened against the variations people actually write; statistical summary helpers like fmt_mean_sd() and fmt_mean_stderr() cover the cell contents clinical tables need. The structural work is largely behind it, including the breaking 2022 move that handed labelling to a sibling package, so what remains is vocabulary coverage.
◆ Prediction
The pattern of adding a SAS format, then a release to handle its variants, suggests the next releases continue filling in format codes and summary helpers rather than changing how formats are applied.
Alternatives to DHARMa and fmtr
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 DHARMa or fmtr.
MetaboAnalystR
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
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
dcurves
Decision curve analysis, settled since 2022 and now moving only when its neighbours do
Recent activity from DHARMa and fmtr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agoDHARMaConditional simulation becomes the GLMM default, changing residuals ⚡
- 10mo agofmtrMean and standard error helper, plus best-format variants
- 11mo agofmtrSAS best. format reimplemented in fapply()
- 1y agoDHARMaDHARMa 0.4.7
- 2y agofmtrQuarter format codes %q and %Q added
- 2y agofmtrFormat lists become readable and writable files
- 2y agofmtrDocumentation and examples expanded
- 2y agofmtrvalue() can return results as a factor
- 3y agoDHARMaDHARMa 0.4.6
- 4y agoDHARMaDHARMa 0.4.5
- 4y agoDHARMaDHARMa 0.4.4
- 5y agoDHARMaDHARMa 0.4.3
Frequently asked questions
What is the difference between DHARMa and fmtr?
Both compete on the same themes — r-package — within Analytics. DHARMa and fmtr 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 DHARMa better than fmtr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. DHARMa and fmtr 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 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.
What are the best alternatives to fmtr?
Top fmtr alternatives in Analytics are ranked by recent ship velocity. Browse the "fmtr alternatives" section above for the current picks, or visit /alternatives/fmtr for the full list with editorial commentary on each.