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easystats @easystats.github.io · Sep 1

... which you can do by adding additional "layers", if you use the gt-format or tinytable-format.

easystats @easystats.github.io · Sep 1

Not sure about the specific requirements for APA 7 style, but I guess you may need some additionally tweaking of the returned table object.

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easystats @easystats.github.io · Sep 1

Wanna dive deeper into the table universe? Check out these links:
👉 easystats.github.io/insight/arti...
👉 vincentarelbundock.github.io/tinytable/

Happy printing, everyone! 🖨️ #rstats #easystats

Formatting, printing and exporting tables

easystats.github.io

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easystats @easystats.github.io · Sep 1

That "tt" option is now fully rolled out across several #easystats packages, powered by the amazing {tinytable} package. This means you can create tables in a gazillion different output formats! How cool is that? 🤯

Example for a colored markdown table, printed to the R console.

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easystats @easystats.github.io · Sep 1

And you can totally control the vibe! Use the `format` argument to get "markdown" (for a classic kable look), "html" (for a sleek gt-table), or the new kid on the block, "tt" (for a tinytable masterpiece!).

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easystats @easystats.github.io · Sep 1

... and when they print, it's thanks to some behind-the-scenes magic with `insight::format_table()` and `insight::export_table()`! ✨

But there's more! Many #easystats functions also have a `display()` method. Think of it as your personal table stylist, making everything look super user-friendly! 💅

Screenshot of the default R console table output

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easystats @easystats.github.io · Sep 1

Alrighty, {easystats} users! 👋 Ever wonder how those neat tables magically appear in your R console, or even better, in your fancy #rstats Markdown and Quarto docs?

Well, most of the objects you work with in {easystats} are basically tables, i.e. a 2D matrix with columns and rows...

library(modelbased)
data(penguins)
model <- lm(body_mass ~ species * island, data = penguins)
out <- estimate_means(model, c("species", "island"))

# basic text output
out

# HTML in viewer pane, using the gt-package
display(out, format = "html")

# tinytable by defaults prints to the viewer pane, too,
# but we change the default to markdown for the console here
options(tinytable_print_output = "markdown")

# nice markdown output in the console, including colored text!
display(out, format = "tt", footer = "") |>
tinytable::style_tt(i = 1:3, color = "#cc0000") |>
tinytable::style_tt(i = 4:6, indent = 2, background = "#009900") |>
tinytable::theme_markdown(ansi = TRUE)

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easystats @easystats.github.io · Aug 31

Even if you're not tackling these super complex questions, {modelbased} is generally just a fantastic tool for really getting your head around your statistical models. Go on, take a peek! You might just fall in love: easystats.github.io/modelbased/

#rstats #easystats #marginaleffects #inference

Estimation of Model-Based Predictions, Contrasts and Means

Implements a general interface for model-based estimations for a wide variety of models, used in the computation of marginal means, contrast analysis and predictions. For a list of supported models, s...

easystats.github.io

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easystats @easystats.github.io · Aug 31

Dealing with interrupted time series where a sudden event just messed with everything?
easystats.github.io/modelbased/a...

Curious about disparities, different trajectories of hidden groups, and what makes them tick?
easystats.github.io/modelbased/a...

Interrupted Time Series Analysis

easystats.github.io

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easystats @easystats.github.io · Aug 31

Got a thing for social and health inequalities?
easystats.github.io/modelbased/a...

Or maybe you're into the nitty-gritty of intersectional analysis?
easystats.github.io/modelbased/a...

Case Study: Measuring and comparing absolute and relative inequalities in R

easystats.github.io

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easystats @easystats.github.io · Aug 31

True to the #easystats vibe, {modelbased} keeps things simple, flexible, and easy-peasy so you can truly unleash the power of your models without pulling your hair out.

Ever wondered about cause and effect in observational data without needing a time machine?
easystats.github.io/modelbased/a...

Case Study: Causal inference for observational data using modelbased

easystats.github.io

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easystats @easystats.github.io · Aug 31

The {modelbased} R package is here to be your statistical sidekick! It's an #rstats gem that helps you squeeze every last drop of insight from your models. It's got a super user-friendly interface to pull out all those estimands from a huge variety of models (doi.org/10.21105/jos...).

modelbased: An R package to make the most out of your statistical models through marginal means, marginal effects, and model predictions

Makowski et al., (2025). modelbased: An R package to make the most out of your statistical models through marginal means, marginal effects, and model predictions. Journal of Open Source Software, 10(1...

doi.org

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easystats @easystats.github.io · Aug 31

Okay, so you've crunched your numbers and got some awesome statistical models? Sometimes, just knowing "X predicts Y" isn't enough to really get to the juicy bits. That's where the cool post-hoc stuff comes in – think estimated marginal means, contrasts, pairwise comparisons, or #marginaleffects.

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Reposted by easystats

Prof Andy Field @profandyfield.com · Aug 20

I’m about halfway through this update (first 11 tutorials are done). I think they’re a lot better. Using a consistent @easystats.github.io workflow throughout will - I think - massively reduce the cognitive load for students. Looking forward to road testing in autumn term.

Prof Andy Field @profandyfield.com · Feb 10

Probably no-one except me uses my R tutorials in their teaching, but if you do, I'm re-writing them over the next 6-9 months. My goal is to streamline them based on 5 years of using them in class, but if you have (polite) requests/suggestsions let me have them. www.discovr.rocks/discovr/

discovr: a package of interactive tutorials | discovr

Statistics education

www.discovr.rocks

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easystats @easystats.github.io · Jul 28

How to summarize the total effect of a categorical variable like education? A new vignette shows how to compute absolute and relative inequality with the #easystats {modelbased}📦in #rstats. Get a single, interpretable number to quantify overall group disparities!
easystats.github.io/modelbased/a...

Case Study: Measuring and comparing absolute and relative inequalities in R

easystats.github.io

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Reposted by easystats

Jarrett Byrnes @jebyrnes.bsky.social · Jul 25

Modelbased for Quick and Beautiful Model Visualization in #rstats imachordata.com/2025/07/25/m... Thanks, @easystats.github.io!

Modelbased for Quick and Beautiful Model Visualization · I'm a Chordata! Urochordata!

imachordata.com

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easystats @easystats.github.io · Jul 22

Just dodging is not yet implemented in {tinyplot}, but hopefully coming soon!

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easystats @easystats.github.io · Jul 22

As you can see, many plot types already work, just some fine-tuning left to do...

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easystats @easystats.github.io · Jul 22

🎉 Great news, R users! 🎉 We're thrilled to announce that {tinyplot} support is coming to the #rstats #easystats project! Get ready for even more amazing stuff to make your data analysis a breeze! 📊✨
@gmcd.bsky.social @vincentab.bsky.social @zeileis.org

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easystats @easystats.github.io · Jul 22

Since `display(format = "tt")` returns a `tinytable` object, you can easily modify the table to meet your needs.

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easystats @easystats.github.io · Jul 22

Here's the default HTML rendering.

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easystats @easystats.github.io · Jul 22

Improved support for the great {tinytable}📦 from @vincentab.bsky.social coming to the easystats packages! Use the `display()` method for different output formats of your tables - HTML, markdown, or - when `format = "tt"` a `tinytable` object that renders context-dependent.
#easystats #rstats

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Reposted by easystats

Dr Mircea Zloteanu ☀️ 🌊🌴 @mzloteanu.bsky.social · Jul 14

#statstab #386 {bayestestR} Evaluating Evidence and Making Decisions using Bayesian Statistics by @mattansb.msbstats.info

Thoughts: Want to start using Bayesian stats? Here is a quick but comprehensive guide in #R

#bayesian #bayes #mcmc #easystats #guide

mattansb.github.io/bayesian-evi...

mattansb.github.io

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Reposted by easystats

tj ♏️ahr @tjmahr.com · Jul 14

bayestestR::describe_posterior() works on rvar columns

screenshot showing the row dataframe with a column of rvars and the markdown-formatted-table output of describe_posterior() + print_md()

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easystats @easystats.github.io · Jul 14

But I think the rvar-support is more recent ;-)