LightNews — News, ranked by scholars

tj mahr 🤘

@tjmahr.com

what a handy page easystats.github.io/effectsize/r...

Interpret Correlation Coefficient — interpret_r

Interpret Correlation Coefficient

easystats.github.io

September 25, 2026 at 6:19 PM

easystats

@easystats.github.io

This year we'll start and try to post one #rstats #easystats function per week, to promote the different packages from the easystats-project. We'll start with `t_to_d()` from the {effectsize} package, which is one of the many functions to convert effectsizes:
easystats.github.io/effectsize/r...

January 6, 2025 at 7:30 AM

Mattan S. Ben-Shachar

@mattansb.msbstats.info

{effectsize} version 1.0.0 has been released! 🍕👹

Not many changes in this update, but his is quite a milestone 🥳 - the second stable package from @easystats.bsky.social, with more to come soon!

#rstats

easystats.github.io/effectsize/

Indices of Effect Size

Provide utilities to work with indices of effect size for a wide variety of models and hypothesis tests (see list of supported models using the function insight::supported_models()), allowing computat...

easystats.github.io

December 10, 2024 at 5:00 PM

Ming Tommy Tang

@tommytang.bsky.social

Significance is not enough! The goal of this package is to provide utilities to work with indices of effect size and standardized parameters, allowing computation and conversion of indices such as Cohen’s d, r, odds-ratios, etc. easystats.github.io/effectsize/ #rstats

December 18, 2024 at 3:15 PM

Mattan S. Ben-Shachar

@mattansb.msbstats.info

The (pooled) sd in Cohen's d can also be thought of as the residual sd when predicting y ~ group.

Compare:
m <- lm(mpg ~ am, data = mtcars)
coef(m)[2] / sigma(m)

effectsize::cohens_d(mpg ~ am, data = mtcars)

October 6, 2025 at 6:31 PM

Dr Mircea Zloteanu 🌺🌞🍃

@mzloteanu.bsky.social

#statstab #396 If researchers find Cohen’s d = 8, no they didn’t

Thoughts: Sometimes an effect is so impressive that its unbelievable.

#effectsize #cohend #QRPs #sesoi

mmmdata.io/posts/2025/0...

July 28, 2025 at 7:47 PM

Mattan S. Ben-Shachar

@mattansb.msbstats.info

lmerTest/brms
easystats' parameters+performance+insight+effectsize
marginaleffects/emmeans

I conduct research analysis for social sciences

October 4, 2024 at 2:49 PM

Ian Hussey

@ianhussey.mmmdata.io

I have a shiny app for students to explore things like this with likert data

errors.shinyapps.io/cohens-d-fro...

<h1>Calculate between subjects Cohen's d from frequencies</h1> <h4>Using the {effectsize} package</h4>

errors.shinyapps.io

February 13, 2026 at 5:58 PM

Daniel 🕹️

@strengejacke.de

Are you a #rstats package developer and want to check whether you used consistent argument names across all functions? Here's a small script (may not always work) that shows all argument names (for functions/methods) used in a package (code in alt-text). Brought to you by "cool but useless"!

$library(effectsize) pkg <- "effectsize" fns <- ls(paste0("package:", pkg)) rds_filepath <- file.path(find.package(pkg), "NAMESPACE") all_fns <- as.data.frame(read.table(rds_filepath)) names(all_fns) <- "func" all_fns <- datawizard::data_filter(all_fns, startsWith(all_fns$func, "S3method(")) fn <- gsub("S3method\$(.*)\$", "\\1", all_fns$func) fn <- gsub(",", ".", fn, fixed = TRUE) all_args <- NULL for (i in fn) { all_args <- c(all_args, formalArgs(getFromNamespace(i, pkg))) } sort(unique(all_args))$

November 19, 2024 at 7:04 PM

Dr Mircea Zloteanu 🌺🌞🍃

@mzloteanu.bsky.social

#statstab #230 Power and Sample Size Determination

Thoughts: Frequentist power is a complicated and non-intuitive thing, so it's good to read various tutorials/papers until you find one that sticks.

#stats #poweranalysis #power #NHST #effectsize

sphweb.bumc.bu.edu/otlt/mph-mod...

Power and Sample Size Determination

sphweb.bumc.bu.edu

November 22, 2024 at 6:52 PM

Mattan S. Ben-Shachar

@mattansb.msbstats.info

For within person effects, @ianhussey.mmmdata.io has this "delicious" benchmark:

easystats.github.io/effectsize/r...

December 9, 2025 at 5:45 PM

Mattan S. Ben-Shachar

@mattansb.msbstats.info

Note that for paired and repeated measures, {effectsize} offers many more options!

easystats.github.io/effectsize/r...

#rstats

Standardized Mean Differences for Repeated Measures — repeated_measures_d

Compute effect size indices for standardized mean differences in repeated measures data. Pair with any reported stats::t.test(paired = TRUE). In a repeated-measures design, the same subjects are meas...

easystats.github.io

February 3, 2025 at 6:04 PM

Dr Mircea Zloteanu 🌺🌞🍃

@mzloteanu.bsky.social

🚨New blog post 📝: Your Study Is Too Small (If You Care About Practically Significant Effects)

#effectsize #precision #poweranalysis #research #Psychology #MCID

open.substack.com/pub/mzlotean...

Your Study Is Too Small (If You Care About Practically Significant Effects)

Power ≠ Precision, the misguided comfort of 80% power

open.substack.com

June 1, 2025 at 12:41 PM

Giulia Calignano

@giuliacalignano.bsky.social

#theory & real #data beyond the mean: distributional overlapping from #effectsize to #permutation
4th Conference #Statistics & #DataScience @SIStatistica
Big 🙏to Nicola Torelli for the invitation ⚡️super coauthors
@ambra-prg.bsky.social & Massimiliano Pastore
🔗https://zenodo.org/records/19415829

April 7, 2026 at 5:05 PM

Dr Mircea Zloteanu 🌺🌞🍃

@mzloteanu.bsky.social

#statstab #210 Effect Sizes for ANOVAs {effectsize}

Thoughts: ANOVAs are rarely what ppl want to report, but if it is then report an effect size! Just mind the % for the CIs 😉

#ANOVA #effectsize #APA #reporting #nonparametric #eta2 #ordinal

easystats.github.io/effectsize/a...

Effect Sizes for ANOVAs

easystats.github.io

October 25, 2024 at 4:23 PM

Dr Mircea Zloteanu 🌺🌞🍃

@mzloteanu.bsky.social

#statstab #398 Eta^2 for bayesian models {effectsize}

Thoughts: Great resource, but scroll to "Eta Squared from Posterior Predictive Distribution"

#effectsize #eta2 #bayesian #brms #r

easystats.github.io/effectsize/r...

$\eta^2$ and Other Effect Size for ANOVA — eta_squared

Functions to compute effect size measures for ANOVAs, such as Eta- ($\eta$), Omega- ($\omega$) and Epsilon- ($\epsilon$) squared, and Cohen's f (or their partialled versions) for ANOVA tables. T...

easystats.github.io

July 30, 2025 at 7:07 PM

Dr Mircea Zloteanu 🌺🌞🍃

@mzloteanu.bsky.social

#statstab #535 The Benefits Of Reporting Critical Effect Size Values

Thoughts: You ran a study w/o a power analysis? Report the lowest value your test could have detected at 80% power and 5% alpha.

#poweranalysis #effectsize #samplesize #posthoc

osf.io/preprints/ps...

OSF

osf.io

May 20, 2026 at 6:02 PM

Mattan S. Ben-Shachar

@mattansb.msbstats.info

Want to write a paper together introducing the new ODD (odd differences delta)?

Title: Isn't that ODD? Bridging the gap between odds ratios and risk differences.

library(marginaleffects)

mod <- glm(
am ~ vs,
family = binomial("logit"),
data = mtcars
)

odds <- avg_predictions(
mod,
variables = "vs",
type = "response",
transform = effectsize::probs_to_odds
)

# odds difference
hypotheses(odds, hypothesis = difference ~ pairwise)

July 31, 2026 at 2:05 PM

Pelagic

@pelagic.bsky.social

Coming soon! Statistics and Data Handling for Biologists by Neil Millar 📖

Learn more and preorder your copy ➡️ https://tinyurl.com/mrxx6vbw

#biology #statistics #statisticssoftware #excel #jamovi #effectsize #poweranalysis

August 21, 2025 at 9:21 AM

Dr Mircea Zloteanu 🌺🌞🍃

@mzloteanu.bsky.social

#statstab #254 Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations

Thoughts: I share tutorial papers, as people resonate with different writing styles and explanations.

#statistics #guide #tutorial #effectsize

link.springer.com/article/10.1...

Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations - European Journal of Epidemiology

Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. A key problem is that there are no interpretations of t...

link.springer.com

January 9, 2025 at 3:11 PM

Lars Henning

@larshenningmd.bsky.social

With all due respect but I lost my former hero Peter Gøtzsche on HPV, I lost you on your messaging during the pandemic. Observational data is bad for evaluating interventions with marginal effectsize. Thats it. History of medicine is a graveyard of plausable interventions that dont work

November 5, 2024 at 6:58 AM

Dr Mircea Zloteanu 🌺🌞🍃

@mzloteanu.bsky.social

#statstab #425 Providing a Lower-Bound Estimate for Psychology’s “Crud Factor”

Thoughts: Psych research may not have the tools to investigate very small effects at all!

#crudfactor #research #psychology #mesurement #error #effectsize

gwern.net/doc/psycholo...

gwern.net

September 26, 2025 at 8:48 PM