mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of goat and modsem — release velocity, themes, recent moves, and the top alternatives to consider.
A gene-set enrichment package that outgrew its human-only origins, then went quiet.
GOAT is a CRAN-published R package for gene set enrichment testing, now at 1.1.4. The visible arc runs from a 2024 beta through a first public CRAN release to a 1.1 line that broadened the package past human gene sets and added persistence for completed analyses. Recent releases are small: the newest ships an igraph handle on plot_network() plus bug fixes.
modsem is grinding latent interaction models toward Mplus parity, one estimator at a time.
modsem fits interaction and quadratic effects between latent variables in R, offering both product-indicator approaches (modsem_pi) and distribution-analytic ones (modsem_da, covering LMS and QML). Releases land roughly monthly and are dense pull-request lists. The recent line is dominated by the LMS approach: gradient refactors, parallel E-steps, composite construct support, and careful handling of residual covariances between latent variables.
GOAT is a CRAN-published R package for gene set enrichment testing, now at 1.1.4. The visible arc runs from a 2024 beta through a first public CRAN release to a 1.1 line that broadened the package past human gene sets and added persistence for completed analyses. Recent releases are small: the newest ships an igraph handle on plot_network() plus bug fixes.
The substantive expansion happened in the 1.1 cycle; everything since has been maintenance and plotting ergonomics. Each release since 1.1 touches one function and returns something callers previously had to reconstruct, which reads as a package settling into a stable API and responding to individual user requests rather than pursuing new scope. The 13-month gap between 1.1.2 and 1.1.4 puts it firmly in low-cadence maintenance.
Expect continued point releases that expose internals from the plotting functions or refresh the bundled GO release, not new analysis capability. The entries give no signal of a planned 1.2.
modsem fits interaction and quadratic effects between latent variables in R, offering both product-indicator approaches (modsem_pi) and distribution-analytic ones (modsem_da, covering LMS and QML). Releases land roughly monthly and are dense pull-request lists. The recent line is dominated by the LMS approach: gradient refactors, parallel E-steps, composite construct support, and careful handling of residual covariances between latent variables.
Two things are being closed at once. The modelling gap — composites and formative constructs, categorical estimators, residual covariances in every direction, multigroup and clustered designs — brings modsem toward what commercial Mplus users expect, and the package's Mplus bridge is maintained alongside it, now with unique file IDs and a cleanup argument. The performance gap is the other: memoised H0, parallel E-step, optimized gradients and Hessians for both LMS and QML, all aimed at the distribution-analytic estimators that are expensive by construction. Convention borrowing from lavaan continues in message formatting and standard-error defaults.
The 1.0.20 and 1.0.21 releases both spent effort on residual covariances between endogenous and exogenous latent variables across estimation, prediction and standardization, and that thread has not obviously closed. The arrival of a second contributor moving MplusAutomation to Suggests suggests dependency trimming continues.
Other Infra & APIs 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 goat or modsem.
mice can finally predict, not just estimate, from multiply imputed data.
A market-microstructure toolkit that keeps adding estimators as the papers land.
A vowel-analysis package trimming dependencies after an email address got it archived.
The R half of the EMU speech database system, fixing what was quietly broken.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
tidyplots keeps rebuilding its own foundations rather than layering around them.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. goat and modsem 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. goat and modsem 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 Infra & APIs products to evaluate alongside.
Top goat alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "goat alternatives" section above for the current picks, or visit /alternatives/goat for the full list with editorial commentary on each.
Top modsem alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "modsem alternatives" section above for the current picks, or visit /alternatives/modsem for the full list with editorial commentary on each.