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discretefdr vs rempsyc

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

Shared themes:r-package

discretefdr vs rempsyc: at a glance

Featurediscretefdrrempsyc
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmultiple-testing, false-discovery-rate, discrete-statistics, r-packageapa-formatting, psychology-research, statistical-tables, ggplot2
Last editorial update5h ago1h ago
WebsiteVisit →Visit →

What is discretefdr?

The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.

DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.

Read the full discretefdr trajectory →

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 →

discretefdr vs rempsyc: editorial side-by-side

D
discretefdr
ANALYTICS
0.0

The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.

◆ Current state

DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.

◆ Where it's heading

The direction is decomposition into a suite. The amnesia dataset went to DiscreteDatasets, summary output now interoperates with the DiscreteTestResults class from DiscreteTests, and match.pvals() stopped being exported — each release trims something that belongs elsewhere. What remains gets methodological additions at a slow, deliberate cadence, with performance work on the step-up procedures that dominate cost when the number of tests is large. Recent activity is maintenance: replacing deprecated calls the package still made of its own siblings. This is a mature statistical package whose release notes are short because the methods underneath them are settled.

◆ Prediction

Expect further alignment with the companion packages rather than new procedures, since the last substantive release was already about interoperating with DiscreteTests classes and the most recent one about clearing deprecations.

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.

Alternatives to discretefdr and rempsyc

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 discretefdr or rempsyc.

See all discretefdr alternatives → · See all rempsyc alternatives →

Recent activity from discretefdr and rempsyc

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

  1. 3mo agodiscretefdrDeprecated internal calls replaced
  2. 11mo agorempsycPoint labels and per-group correlations added to nice_scatter
  3. 1y agodiscretefdrDiscrete Benjamini-Yekutieli procedure added
  4. 1y agorempsycExcel correlation export delegated to the correlation package
  5. 1y agodiscretefdrDatasets split out and step-up procedures sped up
  6. 2y agorempsycTable spacing control and a fix for name collision with afex
  7. 2y agorempsycStandardized coefficients switch to APA 7th edition b* notation
  8. 2y agorempsycLegend and standardization-check fixes
  9. 2y agorempsycnice_table starts coercing model objects automatically

Frequently asked questions

What is the difference between discretefdr and rempsyc?

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

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

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

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.