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Comparison · Analytics

rempsyc vs tbrf

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

Shared themes:r-package

rempsyc vs tbrf: at a glance

Featurerempsyctbrf
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesapa-formatting, psychology-research, statistical-tables, ggplot2rolling-statistics, water-quality, time-series, environmental-data
Last editorial update1h ago44m 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 tbrf?

Time-based rolling statistics for water-quality data, finally getting plotting and padding built in.

tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.

Read the full tbrf trajectory →

rempsyc vs tbrf: 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.

T
tbrf
ANALYTICS
0.0

Time-based rolling statistics for water-quality data, finally getting plotting and padding built in.

◆ Current state

tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.

◆ Where it's heading

The package spent its middle releases absorbing upstream breakage — a lubridate duration redefinition, a tibble 3.0.0 subassignment change, tidyselect internals. The 0.1.7 release breaks that pattern: it is the first in five years to add capability rather than repair it, and it does so by internalising a stat from an abandoned dependency instead of relying on it. Cadence remains very low, with a five-year gap between 0.1.5 and 0.1.6.

◆ Prediction

Absorbing stat_stepribbon() directly suggests further vendoring of the plotting layer rather than new statistical functions. The entries do not indicate which rolling statistics, if any, are queued next.

Alternatives to rempsyc and tbrf

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 tbrf.

See all rempsyc alternatives → · See all tbrf alternatives →

Recent activity from rempsyc and tbrf

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

  1. 11mo agorempsycPoint labels and per-group correlations added to nice_scatter
  2. 0y agotbrfstat_stepribbon vendored in, plus na.pad on all rolling functions
  3. 1y agotbrfgm_mean_ci forwards na.rm and zero.propagate correctly
  4. 1y agorempsycExcel correlation export delegated to the correlation package
  5. 2y agorempsycTable spacing control and a fix for name collision with afex
  6. 2y agorempsycStandardized coefficients switch to APA 7th edition b* notation
  7. 2y agorempsycLegend and standardization-check fixes
  8. 2y agorempsycnice_table starts coercing model objects automatically
  9. 6y agotbrfFix internals broken by tibble 3.0.0 subassignment
  10. 6y agotbrfDate windows recomputed with intervals and periods

Frequently asked questions

What is the difference between rempsyc and tbrf?

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

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

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