Methods and Algorithms for Correlation Analysis in R
By Dominique Makowski, Mattan S. Ben-Shachar, Indrajeet Patil, Daniel Lüdecke. Journal of Open Source Software, 2020
391 citations recorded by the source corpus.
Correlations tests are arguably one of the most commonly used statistical procedures, and are used as a basis in many applications such as exploratory data analysis, structural modelling, data engineering etc. In this context, we present correlation, a toolbox for the R language (R Core Team, 2019) and part of the easystats collection, focused on correlation analysis. Its goal is to be lightweight, easy to use, and allows for the computation of many different kinds of correlations, such as:
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/f35e1e920e7d85dd4b54aadc1b4dc57dadf15778
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Citations in the corpus
- Habits and the electronic herd: The psychology behind social media’s successes and failures (2020, neutral): “The percent of consumers who used a site several times daily was strongly correlated with that site's financial success, r (14) = 0.71, p = .003, based on a hierarchical correla - tion, grouped by site (R Correlations , Makowski et al., 2020).”
- Visualizations with statistical details: The 'ggstatsplot' approach (2021, methodology): “Internally, data cleaning is carried out using the tidyverse (Wickham et al., 2019), while statistical analysis is carried out via the statsExpressions (Patil, 2021) and easysta ts (Ben-Shachar et al., 2020; Lüdecke et al., 2019, 2020, 2021; Makowski et al., 2019, 2020) packages.”
- performance: An R Package for Assessment, Comparison and Testing of Statistical Models (2021, methodology): “…of the easystats ecosystem, which is a collaborative project focused on facilitating simple and intuitive usage of R for statistical analysis (Ben-Shachar et al., 2020; Lüdecke, Ben-Shachar, Patil, Waggoner, et al., 2020; Lüdecke, Ben-Shachar, Patil, & Makowski, 2020; Makowski et al., 2019, 2020).”