I've made this PR:
github.com/easystats/ef...
Let me know if it's okay, how you would like me to credit / link to your work in the dataset docs, or any other change - we can discuss on the PR (:
github.com/easystats/ef...
Let me know if it's okay, how you would like me to credit / link to your work in the dataset docs, or any other change - we can discuss on the PR (:
Desirability by mattansb · Pull Request #685 · easystats/effectsize
library(effectsize)
data("desirability")
head(desirability)
#> participant_id poop chocolate
#> 1 088cf 4 6
#> 2 bcae1 1 7
#> 3 ...
github.com
October 17, 2025 at 11:24 AM
I've made this PR:
github.com/easystats/ef...
Let me know if it's okay, how you would like me to credit / link to your work in the dataset docs, or any other change - we can discuss on the PR (:
github.com/easystats/ef...
Let me know if it's okay, how you would like me to credit / link to your work in the dataset docs, or any other change - we can discuss on the PR (:
Bring your visualizations to life with see, a dynamic R package from the easystats ecosystem that extends ggplot2 to create modern and intuitive graphics.
Visualizations: github.com/easystats/see
Learn more: statisticsglobe.com/online-cours...
#package #datavisualization #tidyverse #analysis
Visualizations: github.com/easystats/see
Learn more: statisticsglobe.com/online-cours...
#package #datavisualization #tidyverse #analysis
September 25, 2025 at 9:38 AM
Bring your visualizations to life with see, a dynamic R package from the easystats ecosystem that extends ggplot2 to create modern and intuitive graphics.
Visualizations: github.com/easystats/see
Learn more: statisticsglobe.com/online-cours...
#package #datavisualization #tidyverse #analysis
Visualizations: github.com/easystats/see
Learn more: statisticsglobe.com/online-cours...
#package #datavisualization #tidyverse #analysis
Reverse suggests dependencies from {marginaleffects} and {bayestestR} from easystats must drive a lot of downloads...
September 21, 2025 at 8:30 AM
Reverse suggests dependencies from {marginaleffects} and {bayestestR} from easystats must drive a lot of downloads...
This is how table printing in #easystats look like - nice tables out-of-the-box thanks to #rstats packages like {gt} or {tinytable}, which is now fully supported across easystats📦
September 1, 2025 at 6:21 AM
This is how table printing in #easystats look like - nice tables out-of-the-box thanks to #rstats packages like {gt} or {tinytable}, which is now fully supported across easystats📦
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
👉 easystats.github.io/insight/arti...
👉 vincentarelbundock.github.io/tinytable/
Happy printing, everyone! 🖨️ #rstats #easystats
Formatting, printing and exporting tables
easystats.github.io
September 1, 2025 at 6:04 AM
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
👉 easystats.github.io/insight/arti...
👉 vincentarelbundock.github.io/tinytable/
Happy printing, everyone! 🖨️ #rstats #easystats
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? 🤯
September 1, 2025 at 6:04 AM
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? 🤯
... 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! 💅
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! 💅
September 1, 2025 at 6:04 AM
... 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! 💅
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! 💅
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...
Well, most of the objects you work with in {easystats} are basically tables, i.e. a 2D matrix with columns and rows...
September 1, 2025 at 6:04 AM
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...
Well, most of the objects you work with in {easystats} are basically tables, i.e. a 2D matrix with columns and rows...
Nice thread that gives examples how many research questions can be answered by some kind of estimated marginal means, contrasts/comparisons or marginal effects.
Check out the recent release from the #rstats {modelbased} 📦 and the cool examples shown in the #easystats thread!
Check out the recent release from the #rstats {modelbased} 📦 and the cool examples shown in the #easystats thread!
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.
August 31, 2025 at 12:54 PM
Nice thread that gives examples how many research questions can be answered by some kind of estimated marginal means, contrasts/comparisons or marginal effects.
Check out the recent release from the #rstats {modelbased} 📦 and the cool examples shown in the #easystats thread!
Check out the recent release from the #rstats {modelbased} 📦 and the cool examples shown in the #easystats thread!
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
#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
August 31, 2025 at 8:27 AM
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
#rstats #easystats #marginaleffects #inference
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...
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
August 31, 2025 at 8:27 AM
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...
Ever wondered about cause and effect in observational data without needing a time machine?
easystats.github.io/modelbased/a...
{easystats} is a very intuitive suite of packages. And their online documentations / vignettes are excellent.
August 30, 2025 at 11:14 AM
{easystats} is a very intuitive suite of packages. And their online documentations / vignettes are excellent.
#easystats was a complete gamechanger for me!
August 21, 2025 at 7:35 PM
#easystats was a complete gamechanger for me!
That's pretty cool seeing the #easystats 📦 in teaching and daily work beyond your own little cosmos #rstats
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.
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/
August 21, 2025 at 9:17 AM
That's pretty cool seeing the #easystats 📦 in teaching and daily work beyond your own little cosmos #rstats
Speaking of which is there a way to go from marginal effects to getting ROPE on the response scale from easystats? To your point might be best to highlight ROPE.
August 16, 2025 at 8:19 PM
Speaking of which is there a way to go from marginal effects to getting ROPE on the response scale from easystats? To your point might be best to highlight ROPE.
I see lots of people use the default value of ROPE provided by easystats to make arguments about effects and I think more thought is needed when using them.
August 16, 2025 at 8:10 PM
I see lots of people use the default value of ROPE provided by easystats to make arguments about effects and I think more thought is needed when using them.
Does bf_restricted from easystats allow you calculate with default priors?
August 16, 2025 at 7:40 PM
Does bf_restricted from easystats allow you calculate with default priors?
As the BF expert on the easystats team, I say: no BFs! Don't give them what they want! They don't know better!
You can show how nice bayestestR (pd, etc.) plays with marginaleffect though ;)
You can show how nice bayestestR (pd, etc.) plays with marginaleffect though ;)
August 16, 2025 at 7:39 PM
As the BF expert on the easystats team, I say: no BFs! Don't give them what they want! They don't know better!
You can show how nice bayestestR (pd, etc.) plays with marginaleffect though ;)
You can show how nice bayestestR (pd, etc.) plays with marginaleffect though ;)
I’m leaning towards just getting rid of it or using easystats.
August 16, 2025 at 7:32 PM
I’m leaning towards just getting rid of it or using easystats.
I wanted to stay in the brms world and not introduce too many packages but for this I will add the easystats package instead.
August 16, 2025 at 5:42 PM
I wanted to stay in the brms world and not introduce too many packages but for this I will add the easystats package instead.
I thought I mentioned easystats for BF calcultions but if not I will add
August 16, 2025 at 5:34 PM
I thought I mentioned easystats for BF calcultions but if not I will add
I can't seem to replicate lmer_alt not working. If you have a reprex, please post it
github.com/easystats/pe...
github.com/easystats/pe...
Add support for afex::lmer_alt · Issue #844 · easystats/performance
See https://sites.google.com/view/jamiecockcroft/blog#h.bv1nxxxwvxwt
github.com
August 4, 2025 at 6:40 AM
I can't seem to replicate lmer_alt not working. If you have a reprex, please post it
github.com/easystats/pe...
github.com/easystats/pe...
Hmmm we ( @easystats.github.io ) definitely should support lmer_alt.
Can you add some info on issues you've encountered?
github.com/easystats/pe...
Can you add some info on issues you've encountered?
github.com/easystats/pe...
August 2, 2025 at 3:27 PM
Hmmm we ( @easystats.github.io ) definitely should support lmer_alt.
Can you add some info on issues you've encountered?
github.com/easystats/pe...
Can you add some info on issues you've encountered?
github.com/easystats/pe...
I think the order that would benefit is likely base-R and then the easystats package. If they need tidy stuff, they would have the skills to learn on their own. For 90%+ of research, I think this will suffice and will teach good statistical habits (checking regression plots, etc.)
August 1, 2025 at 4:00 PM
I think the order that would benefit is likely base-R and then the easystats package. If they need tidy stuff, they would have the skills to learn on their own. For 90%+ of research, I think this will suffice and will teach good statistical habits (checking regression plots, etc.)
They might benefit from something like the easystats packages: easystats.github.io/easystats/
Framework for Easy Statistical Modeling, Visualization, and Reporting
A meta-package that installs and loads a set of packages from easystats ecosystem in a single step. This collection of packages provide a unifying and consistent framework for statistical modeling, vi...
easystats.github.io
July 28, 2025 at 5:00 PM
They might benefit from something like the easystats packages: easystats.github.io/easystats/