pair_chi

Calculates Pearson's Contingency coefficient for every factor variable pair in a dataset.

We provide a tidy data structure and visualisations for multiple or grouped  variable correlations,
general association measures scagnostics and other pairwise scores  suitable for numerical, ordinal and nominal variables.
Supported measures include distance correlation, maximal information, ace correlation, Kendall's tau, and polychoric correlation.

Catherine Hurley

bullseye

Visualising Multiple Pairwise Variable Correlations and Other
Scores

Amit Chinwan

pair_chi function

<dl><dt>d</dt>
<dd>A dataframe</dd>
<dt>handle.na</dt>
<dd>ignored. Pairwise complete observations are used automatically.</dd>
<dt>...</dt>
<dd>other arguments</dd></dl>

Arguments

Pearson's Contingency Coefficient for association between  factors. — pair_chi

<dl>

<dt>d</dt>
<dd>A dataframe</dd>


<dt>handle.na</dt>
<dd>ignored. Pairwise complete observations are used automatically.</dd>


<dt>...</dt>
<dd>other arguments</dd>

</dl>

pair_chi: Pearson's Contingency Coefficient for association between factors.

Description

Usage

Value

Arguments

Details

Examples