print.cluster_analysis

Addresses tasks along the pipeline from raw
data to analysis and visualization for eye-tracking data. Offers several
popular types of analyses, including linear and growth curve time analyses,
onset-contingent reaction time analyses, as well as several non-parametric
bootstrapping approaches. For references to the approach see Mirman,
Dixon & Magnuson (2008) <doi:10.1016/j.jml.2007.11.006>, and
Barr (2008) <doi:10.1016/j.jml.2007.09.002>.

Samuel Forbes

eyetrackingR

Eye-Tracking Data Analysis

Jacob Dink

Brock Ferguson

print.cluster_analysis function

<dl><dt>x</dt>
<dd>The output of the <code>analyze_clusters</code> function</dd>
<dt>...</dt>
<dd>Ignored</dd></dl>

Arguments

Print Method for Cluster Analysis — print.cluster_analysis

<dl>

<dt>x</dt>
<dd>The output of the <code>analyze_clusters</code> function</dd>


<dt>...</dt>
<dd>Ignored</dd>

</dl>

print.cluster_analysis: Print Method for Cluster Analysis

Description

Usage

Value

Arguments