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cfrnow vs ggstatsplot

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

Shared themes:r-package

cfrnow vs ggstatsplot: at a glance

Featurecfrnowggstatsplot
SectorAnalyticsAnalytics
Velocity score5.00.0
Sparks · 30d00
Top themesepidemiology, bayesian-modelling, cfr-estimation, r-packagestatistical-plots, ggplot2, contingency-tables, hypothesis-testing
Last editorial update5h ago1h ago
WebsiteVisit →Visit →

What is cfrnow?

A Bayesian real-time CFR estimator that now ships stratified fits and posterior-predictive checks

cfrnow estimates case fatality ratios from line-list data while an outbreak is still running, using a Bayesian mixture-cure survival model registered as an `epidist` model type. Three releases in a month took it from first public release to stratified, partially-pooled fits with posterior-predictive checking. It leans on `distspec` for delay parameterisation, which reached CRAN alongside the 0.2.1 patch.

Read the full cfrnow trajectory →

What is ggstatsplot?

ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.

ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.

Read the full ggstatsplot trajectory →

cfrnow vs ggstatsplot: editorial side-by-side

C
cfrnow
ANALYTICS
5.0

A Bayesian real-time CFR estimator that now ships stratified fits and posterior-predictive checks

◆ Current state

cfrnow estimates case fatality ratios from line-list data while an outbreak is still running, using a Bayesian mixture-cure survival model registered as an `epidist` model type. Three releases in a month took it from first public release to stratified, partially-pooled fits with posterior-predictive checking. It leans on `distspec` for delay parameterisation, which reached CRAN alongside the 0.2.1 patch.

◆ Where it's heading

The arc runs from producing a single corrected CFR number toward supporting a full model-checking workflow. 0.2.0 added the pieces a modeller needs to defend an estimate: replicate line lists replayed through the real-time truncation, an ascertainment-ratio correction for when fatal and non-fatal cases enter the line list at different rates, and per-group CFRs from `brms` formulas. Delay coverage widened from LogNormal and Gamma to Weibull in the same release.

◆ Prediction

Expect the next release to keep widening covariate and pooling support rather than adding new outcome types, since every 0.2.0 addition extended the existing formula interface instead of replacing it.

G
ggstatsplot
ANALYTICS
0.0

ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.

◆ Current state

ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.

◆ Where it's heading

The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.

◆ Prediction

Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.

Alternatives to cfrnow and ggstatsplot

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 cfrnow or ggstatsplot.

See all cfrnow alternatives → · See all ggstatsplot alternatives →

Recent activity from cfrnow and ggstatsplot

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

  1. 5d agocfrnowdistspec dependency moves to CRAN
  2. 5d agocfrnowStratified CFR fits, Weibull delays, posterior-predictive checks
  3. 1mo agocfrnowFirst release: real-time CFR from a Bayesian mixture-cure model
  4. 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
  5. 4mo agoggstatsplotInternal maintenance only
  6. 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
  7. 8mo agoggstatsplotContributor list updated in DESCRIPTION
  8. 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
  9. 11mo agoggstatsplotAdapted to the latest ggplot2 release

Frequently asked questions

What is the difference between cfrnow and ggstatsplot?

Both compete on the same themes — r-package — within Analytics. cfrnow is currently shipping more aggressively (velocity 5.0 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 cfrnow better than ggstatsplot?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cfrnow is currently shipping more aggressively (velocity 5.0 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 Analytics products to evaluate alongside.

What are the best alternatives to cfrnow?

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

What are the best alternatives to ggstatsplot?

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