← Back to home
Comparison · Analytics

rempsyc vs robma

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

Shared themes:r-package

rempsyc vs robma: at a glance

Featurerempsycrobma
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesapa-formatting, psychology-research, statistical-tables, ggplot2r-package, meta-analysis, bayesian, api-redesign
Last editorial update58m ago4h ago
WebsiteVisit →Visit →

What is rempsyc?

Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.

rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.

Read the full rempsyc trajectory →

What is robma?

RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy

RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.

Read the full robma trajectory →

rempsyc vs robma: editorial side-by-side

R
rempsyc
ANALYTICS
0.0

Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.

◆ Current state

rempsyc produces APA-formatted tables and figures for psychology research — nice_table() for results tables, plus plotting helpers for scatter plots, violin plots, densities and simple slopes. Its releases are CRAN submissions that bundle a long run of development versions, so each entry reads as a digest rather than a single change. The most recent, 0.2.0, added point labelling and per-group correlation statistics to nice_scatter and fixed nice_lm() failing on factor covariates with more than two levels.

◆ Where it's heading

Two forces drive this package and neither is its own roadmap. The first is APA style: when the 7th edition advised against beta for standardized coefficients, the package switched its output to italic b with an asterisk. The second is the surrounding ecosystem — formatting is aligned to what lavaanExtra and afex produce, contrast handling was delegated to easystats' modelbased, and Excel correlation matrix export was handed entirely to the correlation package to cut maintenance.

◆ Prediction

The pattern of delegating functionality to specialist packages while keeping the formatting layer is well established and likely continues. Because releases bundle many small dev versions, the next one will probably again mix plotting refinements with fixes surfaced by upstream changes.

R
robma
ANALYTICS
0.0

RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy

◆ Current state

RoBMA fits robust Bayesian model-averaged meta-analyses that adjust for publication bias. The 3.x line grew by accretion: separate constructors for each model family (RoBMA.reg, NoBMA, BiBMA and their .reg variants), a spike-and-slab algorithm in 3.3.0 that made estimation fast enough to matter, then a steady stream of post-estimation tooling gated on that algorithm — heterogeneity summaries, residuals, funnel plots, z-curve conversion, predict, extract, pooled and adjusted effects. Version 4.0.0 in May 2026 collapses all of it into a unified brma class hierarchy.

◆ Where it's heading

The 3.x series solved the modeling problem and left an interface problem behind: a caller had to know which of six constructors matched their data type, and argument names differed across them. 4.0.0 resolves that by making the model family a set of arguments rather than a function name, and by standardizing input naming on metafor-style conventions. It shipped one day after BayesTools 0.3.0, the author's own upstream infrastructure package, whose new standardization and prior-transformation machinery this rewrite depends on.

◆ Prediction

A rewrite this wide usually needs a follow-up, so expect 4.0.x patches addressing migration gaps as users hit the removed constructors and renamed arguments.

Alternatives to rempsyc and robma

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 rempsyc or robma.

See all rempsyc alternatives → · See all robma alternatives →

Recent activity from rempsyc and robma

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

  1. 3mo agorobmaUnifies six model constructors into one brma class hierarchy
  2. 8mo agorobmaRoBMA 3.6.1
  3. 11mo agorempsycPoint labels and per-group correlations added to nice_scatter
  4. 11mo agorobmaRoBMA 3.6.0
  5. 1y agorobmaRoBMA 3.5.1
  6. 1y agorobmaRoBMA 3.5.0
  7. 1y agorobmaRoBMA 3.4.0
  8. 1y agorempsycExcel correlation export delegated to the correlation package
  9. 2y agorempsycTable spacing control and a fix for name collision with afex
  10. 2y agorempsycStandardized coefficients switch to APA 7th edition b* notation
  11. 2y agorempsycLegend and standardization-check fixes
  12. 2y agorempsycnice_table starts coercing model objects automatically

Frequently asked questions

What is the difference between rempsyc and robma?

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

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

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

What are the best alternatives to robma?

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