Easystats Explained

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Programming Language:R
Operating System:All OS supported by R
Language:English
Genre:Statistical software
License:GPL-3.0

The easystats collection of open source R packages was created in 2019 and primarily includes tools dedicated to the post-processing of statistical models.[1] [2] As of May 2022, the 10 packages composing the easystats ecosystem have been downloaded more than 8 million times, and have been used in more than 1000 scientific publications.[3] [4] [5] The ecosystem is the topic of several statistical courses, video tutorials and books.[6] [7] [8] [9] [10] [11]

The aim of easystats is to provide a unifying and consistent framework to understand and report statistical results. It is also compatible with other collections of packages, such as the tidyverse. Notable design characteristics include its API, with a particular attention given to the names of functions and arguments (e.g., avoiding acronyms and abbreviations), and its low number of dependencies.

History

In 2019, Dominique Makowski contacted software developer Daniel Lüdecke with the idea to collaborate around a collection of R packages aiming at facilitating data science for users without a statistical or computer science background. The first package of easystats, insight was created in 2019, and was envisioned as the foundation of the ecosystem. The second package that emerged, bayestestR, benefitted from the joining of Bayesian expert Mattan S. Ben-Shachar. Other maintainers include Indrajeet Patil and Brenton M. Wiernik.

The easystats collection of packages as a whole received the 2023 Award from the Society for the Improvement of Psychological Science (SIPS).[12]

Packages

The easystats ecosystem contains ten semi-independent packages.

See also

Notes and References

  1. Web site: easystats: one year already. What's next? . r-bloggers . 14 January 2022 . 23 January 2020.
  2. Web site: easystats . GitHub . 14 January 2022 . 14 January 2022.
  3. Web site: easystats Downloads . GitHub . 14 January 2022 . 14 January 2022.
  4. Web site: Project "easystats" . ResearchGate . 16 January 2022.
  5. Web site: Dominique Makowski's Google Scholar Profile . scholar.google.fr.
  6. Web site: easystats: Quickly investigate model performance . Business Science . 17 January 2022 . en . 13 July 2021.
  7. Web site: Automate Textual Reports of Statistical Models in R! report / easystats . YouTube . 17 January 2022 . en.
  8. Book: Field . Andy P. . Discovering statistics using R . 2012 . Thousand Oaks, California . 978-1446200469.
  9. Web site: Analyse des corrélations avec easystats . rzine.fr . 17 January 2022.
  10. Book: Kennedy . Ryan . Introduction to R for social scientists a Tidy programming approach . 2021 . Boca Raton . 9781000353877.
  11. Web site: Monkman . Martin . Data Science with R: A Resource Compendium . 18 May 2022.
  12. Web site: SIPS 2023 Awards Announced! . improvingpsych . 29 September 2023 . 22 August 2023.
  13. Lüdecke . Daniel . Waggoner . Philip D. . Makowski . Dominique . insight: A Unified Interface to Access Information from Model Objects in R . Journal of Open Source Software . 25 June 2019 . 4 . 38 . 1412 . 10.21105/joss.01412 . 2019JOSS....4.1412L . 198640623 . free .
  14. Patil . Indrajeet . Makowski . Dominique . Ben-Shachar . Mattan S. . Wiernik . Brenton M. . Bacher . Etienne . Lüdecke . Daniel . datawizard: An R Package for Easy Data Preparation and Statistical Transformations . Journal of Open Source Software . 9 October 2022 . 7 . 78 . 4684 . 10.21105/joss.04684 . 29 September 2023.
  15. Makowski . Dominique . Ben-Shachar . Mattan . Lüdecke . Daniel . bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework . Journal of Open Source Software . 13 August 2019 . 4 . 40 . 1541 . 10.21105/joss.01541. 2019JOSS....4.1541M . 201882316 . free .
  16. Web site: SIPS Awards . 21 August 2022.
  17. Makowski . Dominique . Ben-Shachar . Mattan . Patil . Indrajeet . Lüdecke . Daniel . Methods and Algorithms for Correlation Analysis in R . Journal of Open Source Software . 16 July 2020 . 5 . 51 . 2306 . 10.21105/joss.02306. 2020JOSS....5.2306M . 225530918 . free .
  18. Lüdecke . Daniel . Ben-Shachar . Mattan . Patil . Indrajeet . Waggoner . Philip . Makowski . Dominique . performance: An R Package for Assessment, Comparison and Testing of Statistical Models . Journal of Open Source Software . 21 April 2021 . 6 . 60 . 3139 . 10.21105/joss.03139. 2021JOSS....6.3139L . 233378359 . free .
  19. Ben-Shachar . Mattan . Lüdecke . Daniel . Makowski . Dominique . effectsize: Estimation of Effect Size Indices and Standardized Parameters . Journal of Open Source Software . 23 December 2020 . 5 . 56 . 2815 . 10.21105/joss.02815. 2020JOSS....5.2815B . 229576898 . free .
  20. Lüdecke . Daniel . Ben-Shachar . Mattan . Patil . Indrajeet . Makowski . Dominique . Extracting, Computing and Exploring the Parameters of Statistical Models using R . Journal of Open Source Software . 9 September 2020 . 5 . 53 . 2445 . 10.21105/joss.02445. 2020JOSS....5.2445L . 225319884 . free .
  21. Lüdecke . Daniel . Patil . Indrajeet . Ben-Shachar . Mattan S. . Wiernik . Brenton M. . Waggoner . Philip . Makowski . Dominique . see: An R Package for Visualizing Statistical Models . Journal of Open Source Software . 6 August 2021 . 6 . 64 . 3393 . 10.21105/joss.03393. 2021JOSS....6.3393L . 238778250 . free .

This article is licensed under the GNU Free Documentation License. It uses material from the Wikipedia article "Easystats".

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