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One function per week, this time with `parameters::model_parameters()`. The function returns a comprehensive, consistent ("tidy") output for regression models and many other statistical procedures, including Bayesian and mixed models. #rstats #easystats easystats.github.io/parameters/r...

submitted 15 hours ago • 1 comment

New tutorial: Causal inference for observational data using propensity scores and g-computation with the {modelbased} package #rstats #easystats easystats.github.io/modelbased/a...

submitted 4 days ago • 1 comment

One function per week, this time we show you `check_itemscale()`, which computes various measures of internal consistencies applied to (sub)scales from items that were extracted using `principal_components()`, or supplied as data frame. #easystats #rstats easystats.github.io/performance/...

submitted 12 days ago • 0 comments

The #easystats team puts lots of work into writing package documentarion and tutorials, available from the GitHub websites. There's also a collection of other resources related to easystats, which we update regularly: easystats.github.io/easystats/ar... let us know if we missed something! #rstats

submitted 15 days ago • 0 comments

One function per week, this week we're excited to show you `model_dashboard()`, the one-ring-to-rule-them-all to get a quick and comprehensive overview of your regression model: easystats.github.io/easystats/re... See example code in the screenshot, and video in next post! #rstats #easystats

submitted 22 days ago • 1 comment

A new version of the #rstats #easystats {modelbased}📦just hit CRAN! {modelbased} helps you to easily compute marginal means, contrast analysis and model predictions. It's a wrapper around the great {marginaleffects}📦, providing an easy and intuitive syntax! easystats.github.io/modelbased/

submitted 22 days ago • 1 comment

We're sorry that we missed to post a function last week, but we're currently in the process of revising our {modelbased}📦 significantly! Look forward to great new features, leveraging the power of {marginaleffects} and {emmeans}, providing an absolutely simple and inuitive user interface! More soon!

submitted 31 days ago • 0 comments

One function per week, this week with `data_seek()` from the {datawizard} package. This function helps you finding variables by their names, variable or value labels in data sets Labelled data is also supported. #easystats #rstats easystats.github.io/datawizard/r...

submitted 31 days ago • 0 comments

One function per week, this week we show you `p_direction()`, the probability of direction, i.e. is a parameter strictly positive or negative? Cum grano salis, a continuous measure of evidence. easystats.github.io/bayestestR/r... #rstats #easystats

submitted 42 days ago • 0 comments

Another #rstats #easystats package is published as "stable" release on CRAN: {datawizard}! The one-stop-solution for so many data wrangling and preparation tasks (reshaping, selecting, filtering, variable standardization, centering, recoding, ...), super light-weight easystats.github.io/datawizard/

submitted 49 days ago • 1 comment

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...

submitted 53 days ago • 1 comment

There's possibly no better statistical programming language than #rstats (note the "possibly", this is not going to be the first language1 versus language2 posts in 2025 😎)

submitted 56 days ago • 1 comment

Also available for frequentist models: easystats.github.io/parameters/r... #rstats #easystats

submitted 63 days ago • 1 comment

These bayes tutorials are the first ones i've actually understood. Looking forward to the rest of the being finished. Go @easystats.bsky.social teams! easystats.github.io/bayestestR/i... #rstats

submitted 71 days ago • 4 comments

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

submitted 72 days ago • 0 comments

A really matured 📦 that reached the 1.0.0 milestone! More #easystats milestone releases to come the next weeks and months... #rstats

submitted 80 days ago • 0 comments

One new feature is how `export_table()` can deal with very wide tables. `export_table()` is used by almost every `print()` method throughout easystats packages. Whenever you have text-output in the console or markdown documents, you can be (almost) sure you won't see messy tables anymore...

submitted 94 days ago • 0 comments

The first stable #easystats release is there! Our "workhorse" package, which builds the foundation of the easystats-ecosystem, has been released in version 1.0.0 on CRAN. Probably not the package users use most, it's rather doing its work silently in the background... easystats.github.io/insight/

submitted 94 days ago • 1 comment

We're thrilled to announce that we’ve begun preparing for the stable (1.0) releases of all packages in our ecosystem. Releases are expected early next year. If you’ve been using any of these packages, we would greatly value your feedback on the API: easystats.github.io/easystats/ #rstats #easystats

submitted 100 days ago • 1 comment

Want to learn/teach R? I'm still actively developing my package of learnr tutorials at github.com/profandyfiel... Just added a tutorial on multilevel models and repeated measures.

submitted 101 days ago • 4 comments

easyverse is growing :-) #easystats #rstats

submitted 101 days ago • 0 comments

And this is how we put it into action! Here you can see the switch from RStudio to Positron by @remi-theriault.com (while @strengejacke.bsky.social is recovering from the evening before...) #rstats #easystats

submitted 104 days ago • 0 comments

This is how the #easystats team generates new ideas for their #rstats packages! Hard(ly) working @remi-theriault.com and @strengejacke.bsky.social!

submitted 104 days ago • 1 comment

Which of the following information below model output (last paragraph, not that one about uncertainty intervals) do you find useful/helpful and think it's worth printing? It's printed once per session. Should some/all information moved into the docs, or kept in output? #easystats

submitted 124 days ago • 3 comments

📚🚨 I posted 11 new chapters of my upcoming book! Model to Meaning: How to Interpret Statistical Results with #marginaleffects for #RStats and Python. These are early drafts and I really need your feedback! Errors, content requests, improvements, etc. marginaleffects.com

submitted 131 days ago • 3 comments

Our Introduction to Bayesian Data Analysis for Cognitive Science (with Nicenboim and Schad) is now in production with CRC Press. It will remain freely available here: bruno.nicenboim.me/bayescogsci/

submitted 132 days ago • 0 comments

{bayestestR} makes it now much easier to process inputs from packages {marginaleffects}, {emmeans}, or random variable types from posterior draws! #easystats #rstats

submitted 132 days ago • 0 comments