create.rs

Creates a response style by cutting up a quadratic monotone spline.

splines

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

create.rs function

<dl><dt>alpha</dt>
<dd>vector of spline coefficients</dd>
<dt>nr.scale</dt>
<dd>number of rating categories; numeric</dd>
<dt>tvec</dt>
<dd>knots for spline functions</dd>
<dt>xvec</dt>
<dd>evaluation points for basis functions</dd>
<dt>scale</dt>
<dd>logical; scale or not</dd></dl>

Arguments

Author

Create a response style — create.rs

<dl>

<dt>alpha</dt>
<dd>vector of spline coefficients</dd>


<dt>nr.scale</dt>
<dd>number of rating categories; numeric</dd>


<dt>tvec</dt>
<dd>knots for spline functions</dd>


<dt>xvec</dt>
<dd>evaluation points for basis functions</dd>


<dt>scale</dt>
<dd>logical; scale or not</dd>

</dl>

create.rs: Create a response style

Description

Usage

Arguments

Author