sensory.aux

Auxiliary Information for <code>sensory</code> Data

datasets

This is an implementation of constrained dual scaling for
detecting response styles in categorical data, including utility functions. The
procedure involves adding additional columns to the data matrix representing the
boundaries between the rating categories. The resulting matrix is then doubled
and analyzed by dual scaling. One-dimensional solutions are sought which provide
optimal scores for the rating categories. These optimal scores are constrained
to follow monotone quadratic splines. Clusters are introduced within which the
response styles can vary. The type of response style present in a cluster can
be diagnosed from the optimal scores for said cluster, and this can be used to
construct an imputed version of the data set which adjusts for response styles.

Pieter Schoonees

Constrained Dual Scaling for Detecting Response Styles

sensory.aux function

A data frame with 268 observations on the following 3 variables.<dl>
<dt>Gender</dt>
<dd>a factor with levels <code>F</code> for females
and <code>M</code> for males</dd>
 <dt>Age</dt>
<dd>a factor for age with levels
<code>14 to 24</code>,<code>25 to 34</code>, <code>35 to 44</code>, and <code>45 to 55</code></dd><dt>Consumption</dt>
<dd>a factor for consumption with levels <code>Heavy
consumer</code>, <code>Light consumer</code>, and <code>Medium consumer</code></dd>
 
</dl>

Format

Auxiliary Information for sensory Data — sensory.aux

A data frame with 268 observations on the following 3 variables.<dl>
<dt>Gender</dt>
<dd>a factor with levels <code>F</code> for females
and <code>M</code> for males</dd>
 <dt>Age</dt>
<dd>a factor for age with levels
<code>14 to 24</code>,<code>25 to 34</code>, <code>35 to 44</code>, and <code>45 to 55</code></dd>

<dt>Consumption</dt>
<dd>a factor for consumption with levels <code>Heavy
consumer</code>, <code>Light consumer</code>, and <code>Medium consumer</code></dd>
 
</dl>

sensory.aux: Auxiliary Information for `sensory` Data

Description

Arguments

Format

Examples