cIRT
A choice-based IRT model published once in 2019 and kept compiling ever since
A side-by-side editorial comparison of DHARMa and epidict — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A spin-out dictionary reader for MSF epidemiological data, finding its shape on CRAN
epidict reads and applies the data dictionaries MSF field epidemiologists use to standardise outbreak and survey datasets. It was split out of the larger sitrep toolchain so the dictionary-reading and variable-renaming functions could ship on CRAN independently. Three releases in roughly two months have taken it from that initial separation to handling intersectional dictionaries.
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.
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.
The next releases will likely broaden brms support past the simple-model restriction and continue converting remaining functions to the formula interface.
epidict reads and applies the data dictionaries MSF field epidemiologists use to standardise outbreak and survey datasets. It was split out of the larger sitrep toolchain so the dictionary-reading and variable-renaming functions could ship on CRAN independently. Three releases in roughly two months have taken it from that initial separation to handling intersectional dictionaries.
The arc is a package being unbundled and then reassembled as its dependencies land on CRAN. The 0.1.0 release deliberately dropped msf_dict_rename_helper() because its dependencies weren't available; 0.2.0 put it back. 0.3.0 is the first release that adds rather than restores, extending intersectional dictionary support and giving callers control over name cleaning.
Expect the next releases to keep widening dictionary coverage rather than changing the API, since the reinstatement work that dominated 0.1.0 to 0.2.0 is now finished.
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 epidict.
A choice-based IRT model published once in 2019 and kept compiling ever since
The R engine behind MetaboAnalyst closes the gap from raw spectra to biological interpretation
Rebuilding SAS's formatting layer in R, one format specification at a time
Standardised coefficients for models where standardising everything is wrong — but the feed only links out
Stream-network spatial models learning to run on data that no longer fits in memory
Bioconductor's installer, frozen at 1.30.x and tuned almost entirely through environment variables
See all DHARMa alternatives → · See all epidict alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. DHARMa and epidict 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. DHARMa and epidict 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.
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.
Top epidict alternatives in Analytics are ranked by recent ship velocity. Browse the "epidict alternatives" section above for the current picks, or visit /alternatives/epidict for the full list with editorial commentary on each.