housing

The <code>housing</code> data frame has 72 rows and 5 columns.
The observations were obtained from an investigation of Satisfaction with housing conditions carried out by the Danish Building Research Institute and the Danish Institute of Mental Health Research.

datasets

Latent budget analysis is a method for the analysis of a two-way
contingency table with an exploratory variable and a response variable. It is
specially designed for compositional data.

Ivan Allaman

Latent Budget Analysis for Compositional Data

housing function

This data frame contains the following columns:<dl>
 <dt>Housing</dt>
<dd>A factor with levels:
 <code>Apartment</code>;
 <code>Atrium</code>;
 <code>Terraced</code>;
 <code>Tower</code>.</dd> <dt>Influence</dt>
<dd>A factor with levels:
 <code>hi</code>;
 <code>low</code>;
 <code>med</code>.</dd> <dt>Contact</dt>
<dd>A factor with levels:
 <code>high</code>;
 <code>low</code>.</dd> <dt>Satisfaction</dt>
<dd>A factor with levels:
 <code>hi</code>;
 <code>low</code>;
 <code>med</code>.</dd>
 
 <dt>value</dt>
<dd>The absolute frequencies of which factor.</dd> 
</dl>

Format

The Satisfaction with Housing Conditions Study — housing

This data frame contains the following columns:<dl>
 <dt>Housing</dt>
<dd>A factor with levels:
 <code>Apartment</code>;
 <code>Atrium</code>;
 <code>Terraced</code>;
 <code>Tower</code>.</dd>

 <dt>Influence</dt>
<dd>A factor with levels:
 <code>hi</code>;
 <code>low</code>;
 <code>med</code>.</dd>

 <dt>Contact</dt>
<dd>A factor with levels:
 <code>high</code>;
 <code>low</code>.</dd>

 <dt>Satisfaction</dt>
<dd>A factor with levels:
 <code>hi</code>;
 <code>low</code>;
 <code>med</code>.</dd>
 
 <dt>value</dt>
<dd>The absolute frequencies of which factor.</dd>

 
</dl>

housing: The Satisfaction with Housing Conditions Study

Description

Usage

Arguments

Format

References