OPCP

This function calculates the Observed Proportion of Concordant Pairs (OPCP) using Kendall's Tau as a measure of association. The pervasive functions also provide the OPCP.

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.

Denis Lajoie

pervasive

Pervasiveness Functions for Correlational Data

OPCP function

<dl><dt>formula</dt>
<dd>A formula specifying the dependent and independent variables.</dd>
<dt>data</dt>
<dd>A data frame containing the variables specified in the formula.</dd></dl>

Arguments

Calculate Observed Proportion of Concordant Pairs (OPCP) — OPCP

<dl>

<dt>formula</dt>
<dd>A formula specifying the dependent and independent variables.</dd>


<dt>data</dt>
<dd>A data frame containing the variables specified in the formula.</dd>

</dl>

OPCP: Calculate Observed Proportion of Concordant Pairs (OPCP)

Description

Usage

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Examples