compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
A side-by-side editorial comparison of stdmod and tidycmprsk — release velocity, themes, recent moves, and the top alternatives to consider.
A moderation-analysis package now pointing users at its own siblings for the harder work.
stdmod computes standardized moderation effects in regression, part of a cluster of R packages from the same author covering moderation, mediation and model comparison. Its release feed is a CRAN-announcement format — several entries carry nothing but a version and a link — and its development has slowed markedly, with the substantive feature work sitting back in 2024. The most recent release is documentation rather than code.
Competing-risks modelling that now moves only when its neighbours do.
tidycmprsk wraps competing risks regression and cumulative incidence estimation in tidy-style output, so results slot into gtsummary tables and ggsurvfit plots. The last two releases are small: 1.1.2 sorts tidy.tidycuminc() output by stratum, 1.1.1 is an HTML5 documentation update for CRAN. The substantive work in the window is 1.1.0, which reorganised the gtsummary relationship.
stdmod computes standardized moderation effects in regression, part of a cluster of R packages from the same author covering moderation, mediation and model comparison. Its release feed is a CRAN-announcement format — several entries carry nothing but a version and a link — and its development has slowed markedly, with the substantive feature work sitting back in 2024. The most recent release is documentation rather than code.
The clearest signal is the latest release redirecting users toward betaselectr and manymome for tasks stdmod also covers, on the grounds that those packages handle them more comprehensively. That is a package consciously narrowing its scope within a family rather than competing with its siblings. The earlier feature work — conditional effects at chosen moderator values, R-squared increase reporting, print formatting — reads as a stable core that has since been left alone.
Expect stdmod to stay in maintenance while the author's newer packages absorb the overlapping functionality, with future releases likely limited to CRAN compliance and documentation.
tidycmprsk wraps competing risks regression and cumulative incidence estimation in tidy-style output, so results slot into gtsummary tables and ggsurvfit plots. The last two releases are small: 1.1.2 sorts tidy.tidycuminc() output by stratum, 1.1.1 is an HTML5 documentation update for CRAN. The substantive work in the window is 1.1.0, which reorganised the gtsummary relationship.
The package has spent its releases handing responsibilities to neighbouring packages rather than growing its own surface. Plotting was deprecated then made defunct in favour of ggsurvfit::ggcuminc(), and 1.1.0 moved the regression table methods so that gtsummary could drop tidycmprsk as a dependency. What remains is the estimation core plus the S3 methods that let other packages consume it, which is a deliberate narrowing.
Expect releases to continue tracking changes in gtsummary and the broader tidy survival stack rather than adding estimation features.
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 stdmod or tidycmprsk.
An MLE package rebuilt around composable solvers, then renamed to match.
nabla dropped its C++ engine to chase exact derivatives at any order.
Eight months from first release to keyring caching and workload identity.
A research-project workflow package where the interesting work is in the plumbing.
A cyclomatic complexity checker that ships once every couple of years, and lands when it does.
Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.
See all stdmod alternatives → · See all tidycmprsk alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. stdmod is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. stdmod is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top stdmod alternatives in Analytics are ranked by recent ship velocity. Browse the "stdmod alternatives" section above for the current picks, or visit /alternatives/stdmod for the full list with editorial commentary on each.
Top tidycmprsk alternatives in Analytics are ranked by recent ship velocity. Browse the "tidycmprsk alternatives" section above for the current picks, or visit /alternatives/tidycmprsk for the full list with editorial commentary on each.