Articles by R on easystats

Compute R2s and other performance indices for all your models!

April 29, 2019 | R on easystats

Indices of model performance (i.e., model quality, goodness of fit, predictive accuracy etc.) are very important, both for model comparison and model description purposes. However, their computation or extraction for a wide variety of models can be complex. To address this, please let us introduce the performance package! performance ...
[Read more...]

Compute R2s and other performance indices for all your models!

April 29, 2019 | R on easystats

Indices of model performance (i.e., model quality, goodness of fit, predictive accuracy etc.) are very important, both for model comparison and model description purposes. However, their computation or extraction for a wide variety of models can be complex. To address this, please let us introduce the performance package! performance ...
[Read more...]

How to easily generate a perfectly normal distribution

April 23, 2019 | R on easystats

Many times, for instance when teaching, I needed to quickly and simply generate a perfectly normally distributed sample to illustrate or show some of its characteristics. This is now very easy to do with the new bayestestR package, which includes the rnorm_perfect function. This function is very similar to ...
[Read more...]

How to easily generate a perfectly normal distribution

April 23, 2019 | R on easystats

Many times, for instance when teaching, I needed to quickly and simply generate a perfectly normally distributed sample to illustrate or show some of its characteristics. This is now very easy to do with the new bayestestR package, which includes the rnorm_perfect function. This function is very similar to ...
[Read more...]

A unified syntax for accessing models’ information

April 1, 2019 | R on easystats

The richness and variety of packages for building and fitting statistical models in R is absolutely astonishing and contributes to the language’s popularity. However, this diversity makes it hard for developpers that want to create tools that work with different types of models. Indeed, the way to access models’ ... [Read more...]

A unified syntax for accessing models’ information

April 1, 2019 | R on easystats

The richness and variety of packages for building and fitting statistical models in R is absolutely astonishing and contributes to the language’s popularity. However, this diversity makes it hard for developpers that want to create tools that work with different types of models. Indeed, the way to access models’ ... [Read more...]

A unified syntax for accessing models’ information

April 1, 2019 | R on easystats

The richness and variety of packages for building and fitting statistical models in R is absolutely astonishing and contributes to the language’s popularity. However, this diversity makes it hard for developpers that want to create tools that work with different types of models. Indeed, the way to access models’ ... [Read more...]

Formatted correlation output with effect sizes

March 27, 2019 | R on easystats

One of the most time-consuming part of data analysis in science is the copy-pasting of specific values of some R output to a manuscript or a report. This task is frustrating, prone to errors, and increases the variability of statistical reporting. At the sime time, standardizing practices of what and ... [Read more...]

The end of errors in ANOVA reporting

March 27, 2019 | R on easystats

Psychological science is still massively using analysis of variance (ANOVA). Despite its relative simplicity, I am very often confronted to errors in its reporting, for instance in student’s theses or manuscripts, or even published papers (See th... [Read more...]

The end of errors in ANOVA reporting

March 27, 2019 | R on easystats

Psychological science is still massively using analysis of variance (ANOVA). Despite its relative simplicity, I am very often confronted to errors in its reporting, for instance in student’s theses or manuscripts, or even published papers (See the excellent statcheck to quickly check the stats of a paper). Beyond the ... [Read more...]

The end of errors in ANOVA reporting

March 27, 2019 | R on easystats

Psychological science is still massively using analysis of variance (ANOVA). Despite its relative simplicity, I am very often confronted to errors in its reporting, for instance in student’s theses or manuscripts, or even published papers (See the excellent statcheck to quickly check the stats of a paper). Beyond the ... [Read more...]

The end of errors in ANOVA reporting

March 27, 2019 | R on easystats

Psychological science is still massively using analysis of variance (ANOVA). Despite its relative simplicity, I am very often confronted to errors in its reporting, for instance in student’s theses or manuscripts, or even published papers (See the excellent statcheck to quickly check the stats of a paper). Beyond the ... [Read more...]

The end of errors in ANOVA reporting

March 27, 2019 | R on easystats

Psychological science is still massively using analysis of variance (ANOVA). Despite its relative simplicity, I am very often confronted to errors in its reporting, for instance in student’s theses or manuscripts, or even published papers (See the excellent statcheck to quickly check the stats of a paper). Beyond the ... [Read more...]
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