Correlation: Methods for Correlation Analysis from the Easystats Ecosystem
by Dominique Makowski
Available on 1 platform
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Description
correlation is a lightweight R package for computing various correlation measures, developed by Dominique Makowski. It is part of the 'easystats' ecosystem and includes methods for partial, Bayesian, multilevel, polychoric, biweight, and distance correlations. The package is referenced in a 2020 paper published in the Journal of Open Source Software.
Use Cases
Calculate partial correlations to control for confounding variables.
Perform Bayesian correlation analysis to incorporate prior knowledge.
Compute multilevel correlations for hierarchical or nested data structures.
Analyze ordinal data using polychoric correlations.
Measure nonlinear associations using distance correlation.
Strengths
Part of the established 'easystats' ecosystem for R.
Implements multiple specialized correlation methods in one package.
Has a peer-reviewed publication reference from 2020.
Limitations
Row count and dataset scale are unknown, which may limit suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
Last update date is unknown; freshness unverified.
Provenance
Source
Dominique Makowski
Collection Method
Likely developed as a software package for statistical analysis.
Time Range
Referenced publication is from 2020.
Freshness
Last update date is unknown.
Geography
Spatial coverage is unknown.
This is a software package (R) for generating correlation data, not a pre-computed static dataset.