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gtsummary vs mrbayes

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

Shared themes:r-package

gtsummary vs mrbayes: at a glance

Featuregtsummarymrbayes
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesclinical-tables, analysis-results-data, regression-summaries, reproducible-reportingmendelian-randomization, bayesian-inference, stan, jags
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is gtsummary?

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

Read the full gtsummary trajectory →

What is mrbayes?

mrbayes spent 2026 auditing its own Bayesian MR estimators for coding errors.

mrbayes wraps Stan and JAGS implementations of Bayesian Mendelian randomization estimators — IVW, MR-Egger, radial Egger, and their multivariable forms. Most of the visible history is packaging work: dependency trimming, conditional examples so the package installs where JAGS will not compile, a maintainer handover. The 0.5.3 release in July 2026 breaks that pattern with a dense list of fixes inside the model code itself.

Read the full mrbayes trajectory →

gtsummary vs mrbayes: editorial side-by-side

G
gtsummary
ANALYTICS
0.0

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

◆ Current state

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

◆ Where it's heading

The ARD work is the through-line. Table IDs exist so gather_ard() can return a named list; hierarchical tables gained per-level sorting and targeted filtering; ARD inputs are pre-processed so sorting applies to non-standard shapes. The package is becoming a structured-results engine that happens to render tables, rather than a renderer alone. Alongside that, 2.2.0 restored data pre-processing that 2.0 had removed after the reduced functionality hurt users — a maintainer willing to reverse a major-version decision.

◆ Prediction

Expect the hierarchical and ARD functions, introduced as a preview without a full deprecation cycle, to keep stabilizing toward a settled API rather than new table types appearing.

M
mrbayes
ANALYTICS
0.0

mrbayes spent 2026 auditing its own Bayesian MR estimators for coding errors.

◆ Current state

mrbayes wraps Stan and JAGS implementations of Bayesian Mendelian randomization estimators — IVW, MR-Egger, radial Egger, and their multivariable forms. Most of the visible history is packaging work: dependency trimming, conditional examples so the package installs where JAGS will not compile, a maintainer handover. The 0.5.3 release in July 2026 breaks that pattern with a dense list of fixes inside the model code itself.

◆ Where it's heading

The package has moved from packaging upkeep into a correctness-audit phase. 0.5.3 fixes a hardcoded three-exposure loop in MVMR-Egger reporting, a broken joint-prior branch, a sigma parameterization error in radial Egger, and several prior specifications — the profile of a maintainer reading their own model files closely rather than responding to bug reports. Platform work continues underneath: an R 4.3.0 floor inherited through a transitive dependency chain, and segfault fixes on macOS ARM.

◆ Prediction

Expect further audit-driven patches to the remaining rjags and Stan model files rather than new estimators; the fixes in 0.5.3 cluster in the Egger variants, which suggests that is where the reading is still in progress.

Alternatives to gtsummary and mrbayes

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 gtsummary or mrbayes.

See all gtsummary alternatives → · See all mrbayes alternatives →

Recent activity from gtsummary and mrbayes

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

  1. 1mo agomrbayesEstimator audit fixes MVMR-Egger loops and radial Egger sigma
  2. 2mo agogtsummaryTheme elements no longer evaluated by default
  3. 8mo agogtsummaryARD strata functions and finer theme control
  4. 11mo agogtsummaryPer-level hierarchical sorting and labeled stacking
  5. 1y agogtsummaryTable splitting, ID labeling, and add_difference_row
  6. 1y agogtsummaryData pre-processing restored after the 2.0 removal
  7. 1y agogtsummarytbl_merge gains explicit merge columns
  8. 1y agomrbayesMVMR rjags example gated on rjags being installed
  9. 1y agomrbayesExamples and tests skip when rstan or rjags is missing
  10. 1y agomrbayespkgdown site updated
  11. 1y agomrbayesHelper command added for installing JAGS
  12. 1y agomrbayesDependency surface trimmed; maintainer handover

Frequently asked questions

What is the difference between gtsummary and mrbayes?

Both compete on the same themes — r-package — within Analytics. gtsummary and mrbayes 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 gtsummary better than mrbayes?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gtsummary and mrbayes 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 gtsummary?

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

What are the best alternatives to mrbayes?

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