Next Article in Journal
Assessing Sustainability Transition in the US Electrical Power System
Previous Article in Journal
Solar-Powered Compaction Garbage Bins in Public Areas: A Preliminary Economic and Environmental Evaluation
Sustainability 2010, 2(2), 533-550; doi:10.3390/su2020533
Article

Statistics for Categorical Surveys—A New Strategy for Multivariate Classification and Determining Variable Importance

Received: 20 December 2009; Accepted: 9 February 2010 / Published: 10 February 2010
Download PDF [329 KB, uploaded 10 February 2010]
Abstract: Surveys can be a rich source of information. However, the extraction of underlying variables from the analysis of mixed categoric and numeric survey data is fraught with complications when using grouping techniques such as clustering or ordination. Here I present a new strategy to deal with classification of households into clusters, and identification of cluster membership for new households. The strategy relies on probabilistic methods for identifying variables underlying the clusters. It incorporates existing methods that (i) help determine the optimal cluster number, (ii) directly identify variables underlying clusters, and (iii) identify the variables important for classifying new cases into existing clusters. The strategy uses the R statistical software, which is freely accessible to anyone.
Keywords: nominal; cluster; typology; statistics; data analysis; decision tree; grouping nominal; cluster; typology; statistics; data analysis; decision tree; grouping
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Herr, A. Statistics for Categorical Surveys—A New Strategy for Multivariate Classification and Determining Variable Importance. Sustainability 2010, 2, 533-550.

AMA Style

Herr A. Statistics for Categorical Surveys—A New Strategy for Multivariate Classification and Determining Variable Importance. Sustainability. 2010; 2(2):533-550.

Chicago/Turabian Style

Herr, Alexander. 2010. "Statistics for Categorical Surveys—A New Strategy for Multivariate Classification and Determining Variable Importance." Sustainability 2, no. 2: 533-550.


Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert