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hdnom vs MVMR

A side-by-side editorial comparison of hdnom and MVMR — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r

hdnom vs MVMR: at a glance

FeaturehdnomMVMR
SectorAnalyticsAnalytics
Velocity score5.00.0
Sparks · 30d00
Top themessurvival analysis, r, regularization, nomogramsmendelian randomization, r, causal inference, genetics
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is hdnom?

hdnom is in pure custodial mode, absorbing glmnet's changes so its users don't have to

hdnom builds nomograms and validation/calibration workflows for high-dimensional Cox survival models on top of glmnet, ncvreg and penalized. The package's own interface has been stable since the 6.0.0 refactor in 2019; every release since has been maintenance. The recent run is entirely about surviving glmnet's evolution — a lambda-selection rule argument, then a cox.ties argument pinning the old tie handling.

Read the full hdnom trajectory →

What is MVMR?

MVMR spent 2026 discovering its own estimators had been returning the wrong numbers

MVMR implements multivariable Mendelian randomization — conditional instrument strength, pleiotropy tests and heterogeneity-robust effect estimation from GWAS summary data. The package has been releasing steadily through 2026, and the substantive releases are all corrections rather than features. Two core routines were found to be computing the wrong quantity outright: qhet_mvmr() built weights from the minimised objective value instead of the minimiser, and strhet_mvmr() never minimised the Q-statistic at all.

Read the full MVMR trajectory →

hdnom vs MVMR: editorial side-by-side

H
hdnom
ANALYTICS
5.0

hdnom is in pure custodial mode, absorbing glmnet's changes so its users don't have to

◆ Current state

hdnom builds nomograms and validation/calibration workflows for high-dimensional Cox survival models on top of glmnet, ncvreg and penalized. The package's own interface has been stable since the 6.0.0 refactor in 2019; every release since has been maintenance. The recent run is entirely about surviving glmnet's evolution — a lambda-selection rule argument, then a cox.ties argument pinning the old tie handling.

◆ Where it's heading

The releases track two upstream pressures with no feature work of its own. glmnet is the larger one: its 4.1-9 change to how Cox cross-validation errors are normalized made lambda.1se select null models far more often, forcing hdnom to expose a rule argument and switch its examples to lambda.min. R-devel is the other, producing a steady trickle of strict-headers, deprecated-symbol and check-note fixes. The pattern is consistent — absorb the upstream change, default to whatever preserves existing behaviour, let users opt into the new one.

◆ Prediction

The cox.ties default is explicitly pinned to "breslow" to silence glmnet's migration warning, which is a deferral rather than a decision; expect a future release to flip that default to "efron" once glmnet completes the transition.

M
MVMR
ANALYTICS
0.0

MVMR spent 2026 discovering its own estimators had been returning the wrong numbers

◆ Current state

MVMR implements multivariable Mendelian randomization — conditional instrument strength, pleiotropy tests and heterogeneity-robust effect estimation from GWAS summary data. The package has been releasing steadily through 2026, and the substantive releases are all corrections rather than features. Two core routines were found to be computing the wrong quantity outright: qhet_mvmr() built weights from the minimised objective value instead of the minimiser, and strhet_mvmr() never minimised the Q-statistic at all.

◆ Where it's heading

This is a sustained audit, not a maintenance drift. Each release since February has fixed a specific analytical defect — omitted intercepts in the exposure-on-genotype regressions, a division by zero when a gencov list held exactly two variants, covariance matrices computed wrongly for matrix inputs, a spurious covariance warning — and several explicitly warn that reported values will differ from previous versions. The strhet_mvmr() rewrite to iteratively reweighted least squares also removes a combinatorial grid that could exhaust memory past three exposures, so the function is now usable as well as correct.

◆ Prediction

The corrections have been walking through the package function by function, and the ones with published fixes so far are the heterogeneity and covariance routines; the remaining untouched estimators are the natural next stop if the audit continues at this pace.

Alternatives to hdnom and MVMR

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 hdnom or MVMR.

See all hdnom alternatives → · See all MVMR alternatives →

Recent activity from hdnom and MVMR

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 18d agohdnomhdnom 6.2.1
  2. 18d agohdnomhdnom 6.2.0 pins Cox tie handling ahead of glmnet's migration
  3. 1mo agoMVMRMVMR rewrites strhet_mvmr() after finding it never minimised Q
  4. 1mo agoMVMRMVMR corrects qhet_mvmr() weights and three covariance bugs
  5. 3mo agoMVMRNew vignette on estimating phenotypic correlations
  6. 3mo agoMVMRMVMR 0.4.5
  7. 4mo agoMVMRMVMR 0.4.4
  8. 5mo agoMVMRMVMR restores intercepts omitted from snpcov_mvmr() regressions
  9. 1y agohdnomhdnom 6.1.0 exposes lambda selection after a glmnet normalization change
  10. 1y agohdnomhdnom 6.0.4
  11. 2y agohdnomhdnom 6.0.3
  12. 3y agohdnomhdnom 6.0.2

Frequently asked questions

What is the difference between hdnom and MVMR?

Both compete on the same themes — r — within Analytics. hdnom is currently shipping more aggressively (velocity 5.0 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.

Is hdnom better than MVMR?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hdnom is currently shipping more aggressively (velocity 5.0 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.

What are the best alternatives to hdnom?

Top hdnom alternatives in Analytics are ranked by recent ship velocity. Browse the "hdnom alternatives" section above for the current picks, or visit /alternatives/hdnom for the full list with editorial commentary on each.

What are the best alternatives to MVMR?

Top MVMR alternatives in Analytics are ranked by recent ship velocity. Browse the "MVMR alternatives" section above for the current picks, or visit /alternatives/mvmr for the full list with editorial commentary on each.