print.circumplex_axes_reliability

Compact display of an <code>axes_reliability()</code> object: the per-axis reliability,
SEm, and Nunnally-Bernstein comparison, with the correlation-as-covariance
standard-error caveat.

Circumplex models, which organize constructs in a circle around two
underlying dimensions, are popular for studying interpersonal functioning,
mood/affect, and vocational preferences/environments. This package provides
tools for analyzing and visualizing circular data, including scoring
functions for relevant instruments and a generalization of the bootstrapped
structural summary method from Zimmermann & Wright (2017)
<doi:10.1177/1073191115621795> and functions for creating publication-ready
tables and figures from the results.

Jeffrey Girard

circumplex

Analysis and Visualization of Circular Data

Johannes Zimmermann

Aidan Wright

print.circumplex_axes_reliability function

<dl><dt>x</dt>
<dd>A <code>circumplex_axes_reliability</code> object.</dd>
<dt>digits</dt>
<dd>The number of decimal places to display (default = 3).</dd>
<dt>...</dt>
<dd>Not used.</dd></dl>

Arguments

Print circumplex axes-reliability results — print.circumplex_axes_reliability

<dl>

<dt>x</dt>
<dd>A <code>circumplex_axes_reliability</code> object.</dd>


<dt>digits</dt>
<dd>The number of decimal places to display (default = 3).</dd>


<dt>...</dt>
<dd>Not used.</dd>

</dl>

print.circumplex_axes_reliability: Print circumplex axes-reliability results

Description

Usage

Value

Arguments