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pervasive  

Pervasiveness Functions for Correlational Data
View on CRAN: Click here


Download and install pervasive package within the R console
Install from CRAN:
install.packages("pervasive")

Install from Github:
library("remotes")
install_github("cran/pervasive")

Install by package version:
library("remotes")
install_version("pervasive", "1.0")



Attach the package and use:
library("pervasive")
Maintained by
Denis Lajoie
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-11-04
Latest Update: 2025-11-04
Description:
Analysis of pervasiveness of effects in correlational data. The Observed Proportion (or Percentage) of Concordant Pairs (OPCP) is Kendall's Tau expressed on a 0 to 1 metric instead of the traditional -1 to 1 metric to facilitate interpretation. As its name implies, it represents the proportion of concordant pairs in a sample (with an adjustment for ties). Pairs are concordant when a participant who has a larger value on a variable than another participant also has a larger value on a second variable. The OPCP is therefore an easily interpretable indicator of monotonicity. The pervasive functions are essentially wrappers for the 'arules' package by Hahsler et al. (2025)<doi:10.32614/CRAN.package.arules> and serve to count individuals who actually display the pattern(s) suggested by a regression. For more details, see the paper "Considering approaches to pervasiveness in the context of personality psychology" now accepted at the journal Personality Science.
How to cite:
Denis Lajoie (2025). pervasive: Pervasiveness Functions for Correlational Data. R package version 1.0, https://cran.r-project.org/web/packages/pervasive. Accessed 06 Jun. 2026.
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