nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
brglm2 vs probmed
A side-by-side editorial comparison of brglm2 and probmed — release velocity, themes, recent moves, and the top alternatives to consider.
brglm2 vs probmed: at a glance
What is brglm2?
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
brglm2 fits generalized linear models using mean and median bias reduction rather than plain maximum likelihood, which matters most when ML estimates are infinite or badly biased. The 0.7-0.9 line broadened coverage — negative binomial via brnb(), ordinal superiority measures, the expo() method for exponentiated parameters, add1()/drop1() so step() stops silently producing nonsense. Version 1.0.0 in August 2025 added mdyplFit(), estimating logistic regression by maximum Diaconis-Ylvisaker prior penalized likelihood with optional high-dimensional corrections. The two releases since have tuned that new path.
What is probmed?
probmed went from one probabilistic effect size to a family of them in sixteen days.
probmed computes P_med, a scale-free probabilistic effect size for causal mediation, as part of the Data-Wise mediationverse alongside medfit, medsim and RMediation. Three releases in three weeks took it from a single estimator to four additional families built on a shared cross-fitted corner-EIF core, covering gauge-calibrated, incremental-elasticity and Sobol variance-share versions of the proportion mediated. Distribution is GitHub and r-universe rather than CRAN, with a load-bearing Remotes pin on medfit.
brglm2 vs probmed: editorial side-by-side
brglm2
0.0ANALYTICS
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
◆ Current state
brglm2 fits generalized linear models using mean and median bias reduction rather than plain maximum likelihood, which matters most when ML estimates are infinite or badly biased. The 0.7-0.9 line broadened coverage — negative binomial via brnb(), ordinal superiority measures, the expo() method for exponentiated parameters, add1()/drop1() so step() stops silently producing nonsense. Version 1.0.0 in August 2025 added mdyplFit(), estimating logistic regression by maximum Diaconis-Ylvisaker prior penalized likelihood with optional high-dimensional corrections. The two releases since have tuned that new path.
◆ Where it's heading
The package's older work assumed the classical regime where observations comfortably outnumber parameters. mdyplFit() and its hd_correction argument target the opposite case, and the follow-up releases are almost entirely about it — Pearson residuals on original responses, aliased parameter handling, the sloe() signal-strength estimator ignoring leverage-one observations. Meanwhile the older surface gets graceful-failure work: brglm_fit() now returns its latest estimates with warnings rather than aborting.
◆ Prediction
Given that 1.0.1 and 1.1.0 are both dominated by mdyplFit follow-ups while the classical path receives only robustness fixes, further work on high-dimensional corrections is the likeliest direction.
probmed
0.0ANALYTICS
probmed went from one probabilistic effect size to a family of them in sixteen days.
◆ Current state
probmed computes P_med, a scale-free probabilistic effect size for causal mediation, as part of the Data-Wise mediationverse alongside medfit, medsim and RMediation. Three releases in three weeks took it from a single estimator to four additional families built on a shared cross-fitted corner-EIF core, covering gauge-calibrated, incremental-elasticity and Sobol variance-share versions of the proportion mediated. Distribution is GitHub and r-universe rather than CRAN, with a load-bearing Remotes pin on medfit.
◆ Where it's heading
The pace is manuscript-driven — estimators arrive with their citations attached and vignettes alongside, and the 0.1.0 notes correct the estimand itself against a manuscript definition rather than fixing a bug in code. Each release adds inference machinery as well as point estimates: percentile-bootstrap intervals and Fieller sets in 0.3.0, a deterministic MBCO interval in 0.2.0 that avoids resampling entirely. The gauge residual and the pmed_sensitivity() helper suggest a growing concern with when the estimand does not decompose at all.
◆ Prediction
0.3.0 shipped a sensitivity helper for shared mediator-outcome confounding and a diagnostic that flags non-decomposability, so the next release most likely extends that diagnostic side rather than adding a fifth estimator family.
Alternatives to brglm2 and probmed
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 brglm2 or probmed.
susier
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
UCell
A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next
detectseparation
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
bayestools
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
robma
RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy
See all brglm2 alternatives → · See all probmed alternatives →
Recent activity from brglm2 and probmed
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoprobmedFour estimator families on a cross-fitted corner-EIF core ⚡
- 2mo agoprobmedParallel mediators and a resampling-free MBCO interval ⚡
- 2mo agoprobmedFirst release: pmed() with the estimand corrected
- 3mo agobrglm2brglm2 v1.1.0
- 8mo agobrglm2brglm2 v1.0.1
- 11mo agobrglm21.0.0 adds maximum DY-prior penalized likelihood for logistic regression ⚡
- 1y agobrglm2brglm2 v0.9.3
- 1y agobrglm2brglm2 v0.9.2
- 3y agobrglm2brglm2 v0.9.1
Frequently asked questions
What is the difference between brglm2 and probmed?
They serve adjacent needs but don't currently overlap on shipped themes. brglm2 and probmed 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 brglm2 better than probmed?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. brglm2 and probmed 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 brglm2?
Top brglm2 alternatives in Analytics are ranked by recent ship velocity. Browse the "brglm2 alternatives" section above for the current picks, or visit /alternatives/brglm2 for the full list with editorial commentary on each.
What are the best alternatives to probmed?
Top probmed alternatives in Analytics are ranked by recent ship velocity. Browse the "probmed alternatives" section above for the current picks, or visit /alternatives/probmed for the full list with editorial commentary on each.