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Comparison · Infra & APIs

jstable vs missSBM

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

Shared themes:r-package

jstable vs missSBM: at a glance

FeaturejstablemissSBM
SectorInfra & APIsInfra & APIs
Velocity score0.02.5
Sparks · 30d00
Top themesbiostatistics, r-package, clinical-research, survey-weightedr-package, network-analysis, stochastic-block-model, missing-data
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is jstable?

A clinical table generator paying down years of edge cases in survey-weighted models

jstable turns regression and survival models into the formatted tables medical papers publish, wrapping coxph, glm, geeglm, lmer and their survey-weighted counterparts. The recent line is almost entirely correction work, concentrated in two places: the .display family and the TableSubgroup family. Version 1.3.25 alone fixed quasibinomial support for survey-weighted logistic regression, automatic factor-to-numeric outcome conversion for svyglm, weighted-versus-original sample counts in the n row, data.table input handling, and Overall column labelling.

Read the full jstable trajectory →

What is missSBM?

missSBM returns after four dormant years with a stricter API and a new refinement step.

The package fits stochastic block models to networks with missing data, covering both missing-at-random and informative sampling designs. After a run of releases from 2019 to 2022, the feed goes quiet until this year's 1.1.0, which breaks the control interface, exposes the block split and merge operations as testable instance methods, and adds a node-swap refinement pass that runs after variational convergence.

Read the full missSBM trajectory →

jstable vs missSBM: editorial side-by-side

J
jstable
INFRA · APIS
0.0

A clinical table generator paying down years of edge cases in survey-weighted models

◆ Current state

jstable turns regression and survival models into the formatted tables medical papers publish, wrapping coxph, glm, geeglm, lmer and their survey-weighted counterparts. The recent line is almost entirely correction work, concentrated in two places: the .display family and the TableSubgroup family. Version 1.3.25 alone fixed quasibinomial support for survey-weighted logistic regression, automatic factor-to-numeric outcome conversion for svyglm, weighted-versus-original sample counts in the n row, data.table input handling, and Overall column labelling.

◆ Where it's heading

Each CRAN release bundles several GitHub patch versions, so the notes read as rolled-up fix lists rather than feature announcements. The substantive thread is pcut.univariate, introduced across seven display functions in 1.3.11 to allow multivariable analysis restricted to significant variables, and repaired repeatedly since as it collided with interaction terms, single-variable selections, clustered models and data.table inputs. The survey-weighted path is the other recurring source: counts, labels and family handling that worked for unweighted data kept failing once weights were involved.

◆ Prediction

Expect further patches in the survey-weighted subgroup functions, since 1.3.25 fixed four separate issues there and each recent release has surfaced more in the same area.

M
missSBM
INFRA · APIS
2.5

missSBM returns after four dormant years with a stricter API and a new refinement step.

◆ Current state

The package fits stochastic block models to networks with missing data, covering both missing-at-random and informative sampling designs. After a run of releases from 2019 to 2022, the feed goes quiet until this year's 1.1.0, which breaks the control interface, exposes the block split and merge operations as testable instance methods, and adds a node-swap refinement pass that runs after variational convergence.

◆ Where it's heading

The new release is maintenance-driven in the best sense: it targets the parts of the codebase that were hard to test or easy to misuse. Replacing free-form control lists with a function of named, defaulted arguments turns silent typos into errors, and pulling the exploration logic out of the collection class makes the search algorithm independently testable without changing it. The polish step addresses a known weakness, reaching individually misclassified nodes that split and merge moves cannot fix.

◆ Prediction

Given the gap before this release, the near-term question is whether the cadence resumes at all; the refactoring it contains would support further algorithmic work if it does.

Alternatives to jstable and missSBM

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 jstable or missSBM.

See all jstable alternatives → · See all missSBM alternatives →

Recent activity from jstable and missSBM

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

  1. 26d agomissSBMReplaces raw control lists with missSBM_param(), adds polish()
  2. 4mo agojstableSurvey-weighted logistic regression and sample counts corrected
  3. 6mo agojstableCompeting-risk counts drawn from original rather than transformed data
  4. 9mo agojstableMulti-state Cox models detected without a manual flag
  5. 10mo agojstableWide fix pass across the display functions
  6. 0y agojstableCrude p-values computed from raw data via data_for_univariate
  7. 1y agojstableSignificance-filtered multivariable analysis added across seven functions
  8. 3y agomissSBMAdapts to Matrix 1.4-2 and fixes HTML5 documentation
  9. 4y agomissSBMFixes linking against nloptR 2.0.0
  10. 5y agomissSBMRelaxes CRAN test tolerances to avoid random failures
  11. 5y agomissSBMRewrites optimisation in C++ armadillo with sparse matrices
  12. 5y agomissSBMRenames core functions and interfaces with the sbm package

Frequently asked questions

What is the difference between jstable and missSBM?

Both compete on the same themes — r-package — within Infra & APIs. missSBM 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.

Is jstable better than missSBM?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. missSBM 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to jstable?

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

What are the best alternatives to missSBM?

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