Articles by R on easystats

New formatting features in the parameters package

October 12, 2020 | R on easystats

You probably already have heard of the parameters package, a light-weight package to extract, compute and explore the parameters of statistical models using R (if not, there is a related publication introducing the package’s main features). In this post, we like to introduce a new feature that facilitates nicely ... [Read more...]

In defence of the 95% CI

May 11, 2020 | R on easystats

TLDR: BayestestR currently uses a 89% threshold by default for Credible Intervals (CI). Should we change that? If so, by what? Join the discussion here. Magical numbers, or conventional thresholds, have bad press in statistics, and there are many of...
[Read more...]

In defence of the 95% CI

May 11, 2020 | R on easystats

TLDR: BayestestR currently uses a 89% threshold by default for Credible Intervals (CI). Should we change that? If so, by what? Join the discussion here. Magical numbers, or conventional thresholds, have bad press in statistics, and there are many of them. For instance, .05 (for the p-value), or the 95% range for the ...
[Read more...]

In defence of the 95% CI

May 11, 2020 | R on easystats

TLDR: BayestestR currently uses a 89% threshold by default for Credible Intervals (CI). Should we change that? If so, by what? Join the discussion here. Magical numbers, or conventional thresholds, have bad press in statistics, and there are many of th... [Read more...]

Multilevel Correlations: A New Method for Common Problems

April 13, 2020 | R on easystats

In this tutorial, we will introduce multilevel correlations (or hierarchical / random-effects correlations) and how to compute them using the new correlations package from the easystats suite. You can install the updated version and load the package as follows:
install.packages("correlation")
library(correlation)
Data Imagine we have an experiment in which 10 individuals completed a ...
[Read more...]

The ulimate package for correlations (by easystats)

March 17, 2020 | R on easystats

The correlation package The easystats project continues to grow with its more recent addition, a package devoted to correlations. Check-out its webpage here! It’s lightweight, easy to use, and allows for the computation of many different kinds of correlations, such as partial correlations, Bayesian correlations, multilevel correlations, polychoric correlations, ...
[Read more...]

The ulimate package for correlations (by easystats)

March 17, 2020 | R on easystats

The correlation package The easystats project continues to grow with its more recent addition, a package devoted to correlations. Check-out its webpage here! It’s lightweight, easy to use, and allows for the computation of many different kinds of correlations, such as partial correlations, Bayesian correlations, multilevel correlations, polychoric correlations, ...
[Read more...]

The p-direction: A Bayesian equivalent of the p-value?

February 25, 2020 | R on easystats

The Bayesian framework is powerful and allows for an incredible amount of flexibility and control over your analysis. That being said, newcomers often struggle with a lot of new concepts and tools and could benefit from some familiar grounding. And the p-value is a very familiar index (although paradoxically often ...
[Read more...]

The p-direction: A Bayesian equivalent of the p-value?

February 25, 2020 | R on easystats

The Bayesian framework is powerful and allows for an incredible amount of flexibility and control over your analysis. That being said, newcomers often struggle with a lot of new concepts and tools and could benefit from some familiar grounding. And the p-value is a very familiar index (although paradoxically often ...
[Read more...]

News from easystats: updated parameters and see packages.

November 24, 2019 | R on easystats

New Features of the parameters and see Package We’re excited to announce some news from the easystats-project. Two packages were updated recently, the parameters-package and our visualization-toolbox, the see-package. Before we start introducing some of the new features, we’d like to explain why you need the see-package to ...
[Read more...]
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