Blog Archives

Describe and understand Bayesian models and posteriors using bayestestR

April 14, 2019
By
Describe and understand Bayesian models and posteriors using bayestestR

The Bayesian framework is quickly gaining popularity among scientists, leading to the growing popularity of packages to fit Bayesian models, such as rstanarm or brms. However, extracting summary indices from these models to report them in your manuscript can be quite challenging, especially for new users. To address this, please let us introduce bayestestR! bayestestR We have recently decided to collaborate around...

Read more »

A unified syntax for accessing models’ information

April 1, 2019
By

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’ internal information (such as parameters names, formulae, data, etc.) is...

Read more »

Formatted correlation output with effect sizes

March 27, 2019
By

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 how to report is crucial for reproducibility and clarity....

Read more »

The end of errors in ANOVA reporting

March 27, 2019
By

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 incomplete or just wrong reporting, one can find a tremendous...

Read more »

The end of errors in ANOVA reporting

March 27, 2019
By

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 incomplete or just wrong reporting, one can find a tremendous...

Read more »

Formatted correlation output with effect sizes

March 24, 2019
By

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 how to report is crucial for reproducibility and clarity....

Read more »

Search R-bloggers


Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)